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---
library_name: peft
tags:
- generated_from_trainer
base_model: openaccess-ai-collective/tiny-mistral
model-index:
- name: mistral-LLM-NER
  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-LLM-NER

This model is a fine-tuned version of [openaccess-ai-collective/tiny-mistral](https://huggingface.co/openaccess-ai-collective/tiny-mistral) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1446

## 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: 0.00025
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 7.9928        | 0.23  | 25   | 5.6978          |
| 3.9614        | 0.45  | 50   | 2.6379          |
| 2.3449        | 0.68  | 75   | 2.0141          |
| 1.9745        | 0.9   | 100  | 1.7486          |
| 1.7972        | 1.13  | 125  | 1.6622          |
| 1.5265        | 1.35  | 150  | 1.6077          |
| 1.3779        | 1.58  | 175  | 1.4895          |
| 1.2514        | 1.8   | 200  | 1.4698          |
| 1.3015        | 2.03  | 225  | 1.4646          |
| 1.1816        | 2.25  | 250  | 1.4042          |
| 1.0834        | 2.48  | 275  | 1.3628          |
| 1.2907        | 2.7   | 300  | 1.3486          |
| 1.4177        | 2.93  | 325  | 1.2939          |
| 1.1508        | 3.15  | 350  | 1.2380          |
| 0.9248        | 3.38  | 375  | 1.2098          |
| 1.0663        | 3.6   | 400  | 1.1924          |
| 1.0292        | 3.83  | 425  | 1.1797          |
| 0.9591        | 4.05  | 450  | 1.1630          |
| 0.837         | 4.28  | 475  | 1.1533          |
| 0.9954        | 4.5   | 500  | 1.1446          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2