transformers safetensors mistral trl sft generated_from_trainer base_model:mistralai/Mistral-7B-Instruct-v0.1 license:apache-2.0 endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.1
tags:
- trl
- sft
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mistral_sparse_80_percent_cola_raw
  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. -->

# mistral_sparse_80_percent_cola_raw

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3881
- Accuracy: 0.8309

## 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-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 0
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4842        | 0.22  | 25   | 0.5429          | 0.7319   |
| 0.5152        | 0.44  | 50   | 0.5166          | 0.7451   |
| 0.4976        | 0.66  | 75   | 0.5337          | 0.7311   |
| 0.4889        | 0.88  | 100  | 0.4847          | 0.7631   |
| 0.4781        | 1.1   | 125  | 0.4716          | 0.7747   |
| 0.4421        | 1.32  | 150  | 0.4569          | 0.7786   |
| 0.4289        | 1.54  | 175  | 0.4589          | 0.7849   |
| 0.4495        | 1.75  | 200  | 0.4373          | 0.7911   |
| 0.417         | 1.97  | 225  | 0.4308          | 0.7903   |
| 0.3719        | 2.19  | 250  | 0.4528          | 0.7950   |
| 0.3746        | 2.41  | 275  | 0.4242          | 0.8114   |
| 0.3942        | 2.63  | 300  | 0.4137          | 0.8176   |
| 0.3603        | 2.85  | 325  | 0.4021          | 0.8215   |
| 0.3509        | 3.07  | 350  | 0.4043          | 0.8184   |
| 0.2865        | 3.29  | 375  | 0.4222          | 0.8277   |
| 0.352         | 3.51  | 400  | 0.4311          | 0.8145   |
| 0.2957        | 3.73  | 425  | 0.3978          | 0.8332   |
| 0.3338        | 3.95  | 450  | 0.3887          | 0.8231   |
| 0.2342        | 4.17  | 475  | 0.4616          | 0.8348   |
| 0.2424        | 4.39  | 500  | 0.4019          | 0.8301   |
| 0.2543        | 4.61  | 525  | 0.4011          | 0.8355   |
| 0.2055        | 4.82  | 550  | 0.4132          | 0.8316   |
| 0.1853        | 5.04  | 575  | 0.3987          | 0.8402   |
| 0.2035        | 5.26  | 600  | 0.4507          | 0.8324   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
