neft-exp3 / README.md
winglian's picture
ep1
522a3bd
---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: out
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# out
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3754
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 6e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9424 | 0.02 | 1 | 1.0092 |
| 1.0216 | 0.2 | 13 | 1.0002 |
| 0.9928 | 0.41 | 26 | 1.0070 |
| 0.9191 | 0.61 | 39 | 1.0096 |
| 0.9276 | 0.81 | 52 | 1.0053 |
| 0.5839 | 1.02 | 65 | 1.0082 |
| 0.5495 | 1.22 | 78 | 1.0552 |
| 0.4987 | 1.42 | 91 | 1.0670 |
| 0.6065 | 1.62 | 104 | 1.0635 |
| 0.5086 | 1.83 | 117 | 1.0656 |
| 0.3216 | 2.03 | 130 | 1.1148 |
| 0.3204 | 2.23 | 143 | 1.1933 |
| 0.2575 | 2.44 | 156 | 1.2069 |
| 0.2721 | 2.64 | 169 | 1.1942 |
| 0.2796 | 2.84 | 182 | 1.2019 |
| 0.1414 | 3.05 | 195 | 1.2782 |
| 0.124 | 3.25 | 208 | 1.3240 |
| 0.1385 | 3.45 | 221 | 1.3561 |
| 0.1077 | 3.66 | 234 | 1.3740 |
| 0.0966 | 3.86 | 247 | 1.3754 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.14.0