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-accum4-lr5e_5-30
  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-accum4-lr5e_5-30

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: 0.5210

## 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: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 30.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8242        | 0.55  | 13   | 1.6628          |
| 1.5291        | 1.57  | 27   | 1.3837          |
| 1.2362        | 2.55  | 40   | 1.1786          |
| 1.1401        | 3.57  | 54   | 1.0978          |
| 1.0666        | 4.55  | 67   | 1.0428          |
| 1.021         | 5.57  | 81   | 1.0063          |
| 0.9852        | 6.55  | 94   | 0.9629          |
| 0.9317        | 7.57  | 108  | 0.9246          |
| 0.8735        | 8.55  | 121  | 0.8885          |
| 0.8147        | 9.57  | 135  | 0.8335          |
| 0.763         | 10.55 | 148  | 0.7860          |
| 0.6926        | 11.57 | 162  | 0.7296          |
| 0.6332        | 12.55 | 175  | 0.6863          |
| 0.5898        | 13.57 | 189  | 0.6491          |
| 0.536         | 14.55 | 202  | 0.6180          |
| 0.5263        | 15.57 | 216  | 0.5764          |
| 0.5071        | 16.55 | 229  | 0.5683          |
| 0.4756        | 17.57 | 243  | 0.5597          |
| 0.4693        | 18.55 | 256  | 0.5342          |
| 0.4414        | 19.57 | 270  | 0.5386          |
| 0.4266        | 20.55 | 283  | 0.5346          |
| 0.4286        | 21.57 | 297  | 0.5155          |
| 0.4256        | 22.55 | 310  | 0.5108          |
| 0.418         | 23.57 | 324  | 0.5230          |
| 0.407         | 24.55 | 337  | 0.5165          |
| 0.411         | 25.57 | 351  | 0.5128          |
| 0.3896        | 26.55 | 364  | 0.5027          |
| 0.39          | 27.57 | 378  | 0.5063          |
| 0.3928        | 28.55 | 391  | 0.4946          |
| 0.3818        | 29.57 | 405  | 0.5063          |


### Framework versions

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