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---
license: other
tags:
- generated_from_trainer
datasets:
- HiTZ/alpaca_mt
model-index:
- name: alpaca-lora-7b-en-pt-es-ca-eu-gl-at
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. -->
# alpaca-lora-7b-en-pt-es-ca-eu-gl-at
This model is a fine-tuned version of [decapoda-research/llama-7b-hf](https://huggingface.co/decapoda-research/llama-7b-hf) on the HiTZ/alpaca_mt ['en', 'pt', 'es', 'ca', 'eu', 'gl', 'at'] dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0667
## 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: 26
- eval_batch_size: 26
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 5
- total_train_batch_size: 130
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3772 | 0.04 | 100 | 1.3860 |
| 1.3043 | 0.07 | 200 | 1.2904 |
| 1.2307 | 0.11 | 300 | 1.2409 |
| 1.2132 | 0.15 | 400 | 1.2086 |
| 1.1987 | 0.19 | 500 | 1.1854 |
| 1.1551 | 0.22 | 600 | 1.1660 |
| 1.1613 | 0.26 | 700 | 1.1516 |
| 1.144 | 0.3 | 800 | 1.1407 |
| 1.1494 | 0.34 | 900 | 1.1297 |
| 1.1072 | 0.37 | 1000 | 1.1196 |
| 1.1302 | 0.41 | 1100 | 1.1117 |
| 1.1074 | 0.45 | 1200 | 1.1058 |
| 1.0846 | 0.48 | 1300 | 1.0995 |
| 1.086 | 0.52 | 1400 | 1.0935 |
| 1.0793 | 0.56 | 1500 | 1.0889 |
| 1.0931 | 0.6 | 1600 | 1.0847 |
| 1.0905 | 0.63 | 1700 | 1.0804 |
| 1.0793 | 0.67 | 1800 | 1.0775 |
| 1.0795 | 0.71 | 1900 | 1.0748 |
| 1.0861 | 0.74 | 2000 | 1.0725 |
| 1.0881 | 0.78 | 2100 | 1.0705 |
| 1.0673 | 0.82 | 2200 | 1.0691 |
| 1.0626 | 0.86 | 2300 | 1.0681 |
| 1.0633 | 0.89 | 2400 | 1.0674 |
| 1.0601 | 0.93 | 2500 | 1.0669 |
| 1.0849 | 0.97 | 2600 | 1.0667 |
### Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2
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