---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: zephyr-7b-sft-lora-accum4-lr5e_5
  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. -->

# zephyr-7b-sft-lora-accum4-lr5e_5

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: 0.5833

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8243        | 0.55  | 13   | 1.6684          |
| 1.5291        | 1.57  | 27   | 1.4003          |
| 1.2355        | 2.55  | 40   | 1.1808          |
| 1.1393        | 3.57  | 54   | 1.0949          |
| 1.0659        | 4.55  | 67   | 1.0457          |
| 1.0196        | 5.57  | 81   | 1.0065          |
| 0.9831        | 6.55  | 94   | 0.9686          |
| 0.9281        | 7.57  | 108  | 0.9255          |
| 0.8678        | 8.55  | 121  | 0.8814          |
| 0.8054        | 9.57  | 135  | 0.8275          |
| 0.7683        | 10.55 | 148  | 0.7861          |
| 0.6906        | 11.57 | 162  | 0.7272          |
| 0.6246        | 12.55 | 175  | 0.6795          |
| 0.5813        | 13.57 | 189  | 0.6364          |
| 0.5253        | 14.55 | 202  | 0.6078          |
| 0.5149        | 15.57 | 216  | 0.5811          |
| 0.4949        | 16.55 | 229  | 0.5605          |
| 0.4644        | 17.57 | 243  | 0.5462          |
| 0.458         | 18.55 | 256  | 0.5346          |
| 0.4294        | 19.57 | 270  | 0.5202          |
| 0.4143        | 20.55 | 283  | 0.5177          |
| 0.4161        | 21.57 | 297  | 0.5108          |
| 0.4128        | 22.55 | 310  | 0.5057          |
| 0.4055        | 23.57 | 324  | 0.5071          |
| 0.3937        | 24.55 | 337  | 0.5058          |
| 0.3967        | 25.57 | 351  | 0.5017          |
| 0.3754        | 26.55 | 364  | 0.4998          |
| 0.3742        | 27.57 | 378  | 0.5019          |
| 0.3756        | 28.55 | 391  | 0.5019          |
| 0.3652        | 29.57 | 405  | 0.5061          |
| 0.3597        | 30.55 | 418  | 0.5076          |
| 0.3609        | 31.57 | 432  | 0.5079          |
| 0.3581        | 32.55 | 445  | 0.5108          |
| 0.3426        | 33.57 | 459  | 0.5117          |
| 0.3481        | 34.55 | 472  | 0.5141          |
| 0.3435        | 35.57 | 486  | 0.5150          |
| 0.3317        | 36.55 | 499  | 0.5245          |
| 0.3387        | 37.57 | 513  | 0.5239          |
| 0.332         | 38.55 | 526  | 0.5319          |
| 0.3334        | 39.57 | 540  | 0.5342          |
| 0.323         | 40.55 | 553  | 0.5388          |
| 0.3144        | 41.57 | 567  | 0.5423          |
| 0.3092        | 42.55 | 580  | 0.5465          |
| 0.3084        | 43.57 | 594  | 0.5481          |
| 0.3091        | 44.55 | 607  | 0.5605          |
| 0.3044        | 45.57 | 621  | 0.5606          |
| 0.303         | 46.55 | 634  | 0.5683          |
| 0.2896        | 47.57 | 648  | 0.5722          |
| 0.2854        | 48.55 | 661  | 0.5778          |
| 0.291         | 49.57 | 675  | 0.5826          |


### Framework versions

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