The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 2 new columns ({'id', 'name'}) and 83 missing columns ({'response_length/min', 'timing_per_token_ms/gen', 'profiling/throughput/elapsed_wall_clock_s', 'profiling/throughput/cumulative_episodes', 'actor/pg_clipfrac_lower', 'training/epoch', 'actor/grad_norm', 'global_seqlen/balanced_min', 'val-aux/success_rate', 'perf/cpu_memory_used_gb', 'critic/advantages/min', 'timing_s/generate_sequences', 'timing_s/stop_profile', 'timing_s/ref', 'timing_s/generation_timing/min', 'timing_s/adv', 'critic/score/mean', 'actor/kl_coef', 'timing_s/step', 'prompt_length/mean', 'global_seqlen/min', 'timing_s/testing', 'timing_per_token_ms/adv', 'timing_s/gen', 'critic/score/max', 'timing_s/reward', 'critic/advantages/max', 'response_length/clip_ratio', 'response_length/mean', 'response_length_non_aborted/clip_ratio', 'response/aborted_ratio', 'actor/ppo_kl', 'perf/total_num_tokens', 'critic/rewards/min', 'prompt_length/max', 'profiling/throughput/episodes_per_second', 'critic/returns/max', 'critic/returns/min', 'actor/entropy', 'critic/rewards/mean', 'response_length_non_aborted/mean', 'profiling/advantage/numel', 'prompt_length/clip_ratio', 'global_seqlen/balanced_max', 'profiling/advantage/batch_size', 'timing_s/update_actor', 'timing_s/generation_timing/topk_ratio', 'profiling/advantage/seq_len', 'response_length/max', 'profiling/generation_cuda_synced_time_s', 'perf/max_memory_allocated_gb', 'response_length_non_aborted/min', 'perf/time_per_step', 'profiling/adv_cuda_synced_time_s', 'timing_per_token_ms/ref', 'global_step', 'actor/lr', 'global_seqlen/mean', 'global_seqlen/minmax_diff', 'prompt_length/min', 'actor/pg_clipfrac', 'critic/score/min', 'actor/kl_loss', 'timing_s/old_log_prob', 'critic/returns/mean', 'perf/actor_update_cuda_synced_time_s', 'profiling/generation_peak_memory_allocated_gb', 'critic/rewards/max', 'profiling/generation_peak_memory_reserved_gb', 'actor/pg_loss', 'perf/mfu/actor', 'perf/max_memory_reserved_gb', 'critic/advantages/mean', 'training/global_step', 'timing_per_token_ms/update_actor', 'val-core/textworld_w2-o3-q1_1-1000/reward/mean@1', 'timing_s/save_checkpoint', 'timing_s/start_profile', 'global_seqlen/max', 'response_length_non_aborted/max', 'perf/throughput', 'profiling/advantage/shape', 'timing_s/generation_timing/max'}).

This happened while the json dataset builder was generating data using

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/tmp/hf-datasets-cache/medium/datasets/65108694865489-config-parquet-and-info-PEARLS-Lab-credit-assignm-999b7518/hub/datasets--PEARLS-Lab--credit-assignment/snapshots/288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q4-token-level-rloo/profiling/profiling_metrics.jsonl (origin=hf://datasets/PEARLS-Lab/credit-assignment@288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q4-token-level-rloo/profiling/profiling_metrics.jsonl), /tmp/hf-datasets-cache/medium/datasets/65108694865489-config-parquet-and-info-PEARLS-Lab-credit-assignm-999b7518/hub/datasets--PEARLS-Lab--credit-assignment/snapshots/288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q4-token-level-rloo/wandb_run_info.json (origin=hf://datasets/PEARLS-Lab/credit-assignment@288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q4-token-level-rloo/wandb_run_info.json)]

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 675, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              id: string
              name: string
              to
              {'global_step': Value('int64'), 'profiling/generation_peak_memory_allocated_gb': Value('float64'), 'profiling/generation_peak_memory_reserved_gb': Value('float64'), 'profiling/generation_cuda_synced_time_s': Value('float64'), 'global_seqlen/min': Value('int64'), 'global_seqlen/max': Value('int64'), 'global_seqlen/minmax_diff': Value('int64'), 'global_seqlen/balanced_min': Value('int64'), 'global_seqlen/balanced_max': Value('int64'), 'global_seqlen/mean': Value('float64'), 'actor/entropy': Value('float64'), 'profiling/adv_cuda_synced_time_s': Value('float64'), 'actor/kl_loss': Value('float64'), 'actor/kl_coef': Value('float64'), 'actor/pg_loss': Value('float64'), 'actor/pg_clipfrac': Value('float64'), 'actor/ppo_kl': Value('float64'), 'actor/pg_clipfrac_lower': Value('float64'), 'actor/grad_norm': Value('float64'), 'perf/mfu/actor': Value('float64'), 'perf/actor_update_cuda_synced_time_s': Value('float64'), 'perf/max_memory_allocated_gb': Value('float64'), 'perf/max_memory_reserved_gb': Value('float64'), 'perf/cpu_memory_used_gb': Value('float64'), 'actor/lr': Value('float64'), 'training/global_step': Value('int64'), 'training/epoch': Value('int64'), 'critic/score/mean': Value('float64'), 'critic/score/max': Value('float64'), 'critic/score/min': Value('float64'), 'critic/rewards/mean': Value('float64'), 'critic/rewards/max': Value('float64'), 'critic/rewards/min': Value('float64'), 'critic/advantages/mean': Value('float64'), 'critic/advantages/max': Value('float64'), 'critic/a
              ...
              : Value('float64'), 'prompt_length/clip_ratio': Value('float64'), 'timing_s/start_profile': Value('float64'), 'timing_s/generate_sequences': Value('float64'), 'timing_s/generation_timing/max': Value('float64'), 'timing_s/generation_timing/min': Value('float64'), 'timing_s/generation_timing/topk_ratio': Value('float64'), 'timing_s/gen': Value('float64'), 'timing_s/reward': Value('float64'), 'timing_s/old_log_prob': Value('float64'), 'timing_s/ref': Value('float64'), 'timing_s/adv': Value('float64'), 'timing_s/update_actor': Value('float64'), 'timing_s/step': Value('float64'), 'timing_s/stop_profile': Value('float64'), 'timing_per_token_ms/gen': Value('float64'), 'timing_per_token_ms/update_actor': Value('float64'), 'timing_per_token_ms/adv': Value('float64'), 'timing_per_token_ms/ref': Value('float64'), 'perf/total_num_tokens': Value('int64'), 'perf/time_per_step': Value('float64'), 'perf/throughput': Value('float64'), 'profiling/advantage/numel': Value('int64'), 'profiling/advantage/shape': Value('string'), 'profiling/advantage/batch_size': Value('int64'), 'profiling/advantage/seq_len': Value('int64'), 'profiling/throughput/cumulative_episodes': Value('int64'), 'profiling/throughput/elapsed_wall_clock_s': Value('float64'), 'profiling/throughput/episodes_per_second': Value('float64'), 'val-core/textworld_w2-o3-q1_1-1000/reward/mean@1': Value('float64'), 'val-aux/success_rate': Value('float64'), 'timing_s/testing': Value('float64'), 'timing_s/save_checkpoint': Value('float64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1889, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 2 new columns ({'id', 'name'}) and 83 missing columns ({'response_length/min', 'timing_per_token_ms/gen', 'profiling/throughput/elapsed_wall_clock_s', 'profiling/throughput/cumulative_episodes', 'actor/pg_clipfrac_lower', 'training/epoch', 'actor/grad_norm', 'global_seqlen/balanced_min', 'val-aux/success_rate', 'perf/cpu_memory_used_gb', 'critic/advantages/min', 'timing_s/generate_sequences', 'timing_s/stop_profile', 'timing_s/ref', 'timing_s/generation_timing/min', 'timing_s/adv', 'critic/score/mean', 'actor/kl_coef', 'timing_s/step', 'prompt_length/mean', 'global_seqlen/min', 'timing_s/testing', 'timing_per_token_ms/adv', 'timing_s/gen', 'critic/score/max', 'timing_s/reward', 'critic/advantages/max', 'response_length/clip_ratio', 'response_length/mean', 'response_length_non_aborted/clip_ratio', 'response/aborted_ratio', 'actor/ppo_kl', 'perf/total_num_tokens', 'critic/rewards/min', 'prompt_length/max', 'profiling/throughput/episodes_per_second', 'critic/returns/max', 'critic/returns/min', 'actor/entropy', 'critic/rewards/mean', 'response_length_non_aborted/mean', 'profiling/advantage/numel', 'prompt_length/clip_ratio', 'global_seqlen/balanced_max', 'profiling/advantage/batch_size', 'timing_s/update_actor', 'timing_s/generation_timing/topk_ratio', 'profiling/advantage/seq_len', 'response_length/max', 'profiling/generation_cuda_synced_time_s', 'perf/max_memory_allocated_gb', 'response_length_non_aborted/min', 'perf/time_per_step', 'profiling/adv_cuda_synced_time_s', 'timing_per_token_ms/ref', 'global_step', 'actor/lr', 'global_seqlen/mean', 'global_seqlen/minmax_diff', 'prompt_length/min', 'actor/pg_clipfrac', 'critic/score/min', 'actor/kl_loss', 'timing_s/old_log_prob', 'critic/returns/mean', 'perf/actor_update_cuda_synced_time_s', 'profiling/generation_peak_memory_allocated_gb', 'critic/rewards/max', 'profiling/generation_peak_memory_reserved_gb', 'actor/pg_loss', 'perf/mfu/actor', 'perf/max_memory_reserved_gb', 'critic/advantages/mean', 'training/global_step', 'timing_per_token_ms/update_actor', 'val-core/textworld_w2-o3-q1_1-1000/reward/mean@1', 'timing_s/save_checkpoint', 'timing_s/start_profile', 'global_seqlen/max', 'response_length_non_aborted/max', 'perf/throughput', 'profiling/advantage/shape', 'timing_s/generation_timing/max'}).
              
              This happened while the json dataset builder was generating data using
              
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/tmp/hf-datasets-cache/medium/datasets/65108694865489-config-parquet-and-info-PEARLS-Lab-credit-assignm-999b7518/hub/datasets--PEARLS-Lab--credit-assignment/snapshots/288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q2-full-traj-rloo/profiling/profiling_metrics.jsonl (origin=hf://datasets/PEARLS-Lab/credit-assignment@288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q2-full-traj-rloo/profiling/profiling_metrics.jsonl), /tmp/hf-datasets-cache/medium/datasets/65108694865489-config-parquet-and-info-PEARLS-Lab-credit-assignm-999b7518/hub/datasets--PEARLS-Lab--credit-assignment/snapshots/288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q2-full-traj-rloo/wandb_run_info.json (origin=hf://datasets/PEARLS-Lab/credit-assignment@288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q2-full-traj-rloo/wandb_run_info.json), 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/tmp/hf-datasets-cache/medium/datasets/65108694865489-config-parquet-and-info-PEARLS-Lab-credit-assignm-999b7518/hub/datasets--PEARLS-Lab--credit-assignment/snapshots/288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q2-turn-level-ppo/profiling/profiling_metrics.jsonl (origin=hf://datasets/PEARLS-Lab/credit-assignment@288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q2-turn-level-ppo/profiling/profiling_metrics.jsonl), /tmp/hf-datasets-cache/medium/datasets/65108694865489-config-parquet-and-info-PEARLS-Lab-credit-assignm-999b7518/hub/datasets--PEARLS-Lab--credit-assignment/snapshots/288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q2-turn-level-ppo/wandb_run_info.json (origin=hf://datasets/PEARLS-Lab/credit-assignment@288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q2-turn-level-ppo/wandb_run_info.json), 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/tmp/hf-datasets-cache/medium/datasets/65108694865489-config-parquet-and-info-PEARLS-Lab-credit-assignm-999b7518/hub/datasets--PEARLS-Lab--credit-assignment/snapshots/288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q4-token-level-rloo/profiling/profiling_metrics.jsonl (origin=hf://datasets/PEARLS-Lab/credit-assignment@288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q4-token-level-rloo/profiling/profiling_metrics.jsonl), /tmp/hf-datasets-cache/medium/datasets/65108694865489-config-parquet-and-info-PEARLS-Lab-credit-assignm-999b7518/hub/datasets--PEARLS-Lab--credit-assignment/snapshots/288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q4-token-level-rloo/wandb_run_info.json (origin=hf://datasets/PEARLS-Lab/credit-assignment@288e79c798ed6355ce088065e0aad27b11e74666/checkpoints/multi-turn-credit-assign/qwen-2.5-1.5b-q4-token-level-rloo/wandb_run_info.json)]
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

global_step
int64
profiling/generation_peak_memory_allocated_gb
float64
profiling/generation_peak_memory_reserved_gb
float64
profiling/generation_cuda_synced_time_s
float64
global_seqlen/min
int64
global_seqlen/max
int64
global_seqlen/minmax_diff
int64
global_seqlen/balanced_min
int64
global_seqlen/balanced_max
int64
global_seqlen/mean
float64
actor/entropy
float64
profiling/adv_cuda_synced_time_s
float64
actor/kl_loss
float64
actor/kl_coef
float64
actor/pg_loss
float64
actor/pg_clipfrac
float64
actor/ppo_kl
float64
actor/pg_clipfrac_lower
float64
actor/grad_norm
float64
perf/mfu/actor
float64
perf/actor_update_cuda_synced_time_s
float64
perf/max_memory_allocated_gb
float64
perf/max_memory_reserved_gb
float64
perf/cpu_memory_used_gb
float64
actor/lr
float64
training/global_step
int64
training/epoch
int64
critic/score/mean
float64
critic/score/max
float64
critic/score/min
float64
critic/rewards/mean
float64
critic/rewards/max
float64
critic/rewards/min
float64
critic/advantages/mean
float64
critic/advantages/max
float64
critic/advantages/min
float64
critic/returns/mean
float64
critic/returns/max
float64
critic/returns/min
float64
response_length/mean
float64
response_length/max
float64
response_length/min
float64
response_length/clip_ratio
float64
response_length_non_aborted/mean
float64
response_length_non_aborted/max
float64
response_length_non_aborted/min
float64
response_length_non_aborted/clip_ratio
float64
response/aborted_ratio
float64
prompt_length/mean
float64
prompt_length/max
float64
prompt_length/min
float64
prompt_length/clip_ratio
float64
timing_s/start_profile
float64
timing_s/generate_sequences
float64
timing_s/generation_timing/max
float64
timing_s/generation_timing/min
float64
timing_s/generation_timing/topk_ratio
float64
timing_s/gen
float64
timing_s/reward
float64
timing_s/old_log_prob
float64
timing_s/ref
float64
timing_s/adv
float64
timing_s/update_actor
float64
timing_s/step
float64
timing_s/stop_profile
float64
timing_per_token_ms/gen
float64
timing_per_token_ms/update_actor
float64
timing_per_token_ms/adv
float64
timing_per_token_ms/ref
float64
perf/total_num_tokens
int64
perf/time_per_step
float64
perf/throughput
float64
profiling/advantage/numel
int64
profiling/advantage/shape
string
profiling/advantage/batch_size
int64
profiling/advantage/seq_len
int64
profiling/throughput/cumulative_episodes
int64
profiling/throughput/elapsed_wall_clock_s
float64
profiling/throughput/episodes_per_second
float64
val-core/textworld_w2-o3-q1_1-1000/reward/mean@1
float64
val-aux/success_rate
float64
timing_s/testing
float64
timing_s/save_checkpoint
null
1
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End of preview.