---
license: other
base_model: baffo32/decapoda-research-llama-7B-hf
tags:
- generated_from_trainer
model-index:
- name: llama-7b-absa-MT-restaurants
  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. -->

# llama-7b-absa-MT-restaurants

This model is a fine-tuned version of [baffo32/decapoda-research-llama-7B-hf](https://huggingface.co/baffo32/decapoda-research-llama-7B-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0032

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 1200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.089         | 0.13  | 40   | 0.0323          |
| 0.0253        | 0.25  | 80   | 0.0248          |
| 0.0231        | 0.38  | 120  | 0.0213          |
| 0.0214        | 0.51  | 160  | 0.0194          |
| 0.017         | 0.63  | 200  | 0.0153          |
| 0.0162        | 0.76  | 240  | 0.0137          |
| 0.0129        | 0.89  | 280  | 0.0141          |
| 0.0119        | 1.01  | 320  | 0.0119          |
| 0.0079        | 1.14  | 360  | 0.0109          |
| 0.0072        | 1.27  | 400  | 0.0113          |
| 0.0074        | 1.39  | 440  | 0.0099          |
| 0.006         | 1.52  | 480  | 0.0091          |
| 0.0067        | 1.65  | 520  | 0.0078          |
| 0.0046        | 1.77  | 560  | 0.0091          |
| 0.0055        | 1.9   | 600  | 0.0064          |
| 0.0032        | 2.03  | 640  | 0.0058          |
| 0.002         | 2.15  | 680  | 0.0066          |
| 0.002         | 2.28  | 720  | 0.0061          |
| 0.0018        | 2.41  | 760  | 0.0063          |
| 0.0018        | 2.53  | 800  | 0.0057          |
| 0.0021        | 2.66  | 840  | 0.0048          |
| 0.0017        | 2.78  | 880  | 0.0046          |
| 0.0013        | 2.91  | 920  | 0.0044          |
| 0.0008        | 3.04  | 960  | 0.0036          |
| 0.0005        | 3.16  | 1000 | 0.0043          |
| 0.0004        | 3.29  | 1040 | 0.0042          |
| 0.0004        | 3.42  | 1080 | 0.0036          |
| 0.0004        | 3.54  | 1120 | 0.0039          |
| 0.0003        | 3.67  | 1160 | 0.0034          |
| 0.0002        | 3.8   | 1200 | 0.0032          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2