transformers tensorboard safetensors mistral text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: runs
  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. -->

# runs

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1137
- Accuracy: 0.0000

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 48
- seed: 444
- gradient_accumulation_steps: 3
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.3
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.03  | 10   | 4.7890          | 0.1380   |
| 4.9326        | 0.05  | 20   | 4.4600          | 0.1310   |
| 4.9326        | 0.08  | 30   | 4.1364          | 0.0172   |
| 4.1299        | 0.11  | 40   | 3.7156          | 0.0010   |
| 4.1299        | 0.13  | 50   | 3.3965          | 0.0002   |
| 3.4428        | 0.16  | 60   | 3.2530          | 0.0002   |
| 3.4428        | 0.19  | 70   | 3.1727          | 0.0000   |
| 3.1873        | 0.21  | 80   | 3.1316          | 0.0000   |
| 3.1873        | 0.24  | 90   | 3.1165          | 0.0000   |
| 3.1176        | 0.26  | 100  | 3.1137          | 0.0000   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
