safetensors generated_from_trainer base_model:mistralai/Mistral-7B-v0.1 license:apache-2.0 region:us
---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: zephyr-7b-sft-lora-accum8-lr1e_6
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# zephyr-7b-sft-lora-accum8-lr1e_6

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8034

## 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: 1e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 50.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0856        | 0.51  | 6    | 2.0622          |
| 2.0731        | 1.53  | 13   | 2.0591          |
| 2.0751        | 2.55  | 20   | 2.0578          |
| 2.0677        | 3.57  | 27   | 2.0556          |
| 2.0744        | 4.51  | 33   | 2.0476          |
| 2.0611        | 5.53  | 40   | 2.0437          |
| 2.051         | 6.55  | 47   | 2.0360          |
| 2.0559        | 7.57  | 54   | 2.0278          |
| 2.0429        | 8.51  | 60   | 2.0241          |
| 2.0373        | 9.53  | 67   | 2.0169          |
| 2.027         | 10.55 | 74   | 2.0083          |
| 2.0231        | 11.57 | 81   | 1.9966          |
| 2.0053        | 12.51 | 87   | 1.9906          |
| 2.0102        | 13.53 | 94   | 1.9815          |
| 1.989         | 14.55 | 101  | 1.9756          |
| 1.9901        | 15.57 | 108  | 1.9675          |
| 1.9893        | 16.51 | 114  | 1.9577          |
| 1.969         | 17.53 | 121  | 1.9478          |
| 1.9607        | 18.55 | 128  | 1.9387          |
| 1.9522        | 19.57 | 135  | 1.9304          |
| 1.9454        | 20.51 | 141  | 1.9281          |
| 1.9416        | 21.53 | 148  | 1.9205          |
| 1.9265        | 22.55 | 155  | 1.9154          |
| 1.9286        | 23.57 | 162  | 1.9079          |
| 1.921         | 24.51 | 168  | 1.9001          |
| 1.9082        | 25.53 | 175  | 1.8921          |
| 1.9102        | 26.55 | 182  | 1.8856          |
| 1.9072        | 27.57 | 189  | 1.8808          |
| 1.898         | 28.51 | 195  | 1.8763          |
| 1.885         | 29.53 | 202  | 1.8710          |
| 1.896         | 30.55 | 209  | 1.8660          |
| 1.8813        | 31.57 | 216  | 1.8625          |
| 1.8819        | 32.51 | 222  | 1.8561          |
| 1.8627        | 33.53 | 229  | 1.8486          |
| 1.8683        | 34.55 | 236  | 1.8457          |
| 1.8671        | 35.57 | 243  | 1.8423          |
| 1.86          | 36.51 | 249  | 1.8396          |
| 1.8573        | 37.53 | 256  | 1.8334          |
| 1.847         | 38.55 | 263  | 1.8330          |
| 1.842         | 39.57 | 270  | 1.8292          |
| 1.8437        | 40.51 | 276  | 1.8254          |
| 1.8406        | 41.53 | 283  | 1.8224          |
| 1.8369        | 42.55 | 290  | 1.8169          |
| 1.8345        | 43.57 | 297  | 1.8179          |
| 1.8418        | 44.51 | 303  | 1.8128          |
| 1.8315        | 45.53 | 310  | 1.8125          |
| 1.8243        | 46.55 | 317  | 1.8103          |
| 1.8312        | 47.57 | 324  | 1.8057          |
| 1.8247        | 48.51 | 330  | 1.8047          |
| 1.8189        | 49.53 | 337  | 1.8032          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
