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README.md
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---
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license: other
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tags:
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- generated_from_trainer
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model-index:
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- name: alpaca-lora-13b-en-pt-es-ca-eu-gl-at
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# alpaca-lora-13b-en-pt-es-ca-eu-gl-at
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This model is a fine-tuned version of [decapoda-research/llama-13b-hf](https://huggingface.co/decapoda-research/llama-13b-hf) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9967
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0003
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.03
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- num_epochs: 1
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 1.303 | 0.04 | 100 | 1.2875 |
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| 1.2153 | 0.07 | 200 | 1.2016 |
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| 1.1584 | 0.11 | 300 | 1.1560 |
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| 1.1426 | 0.15 | 400 | 1.1277 |
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| 1.1198 | 0.18 | 500 | 1.1063 |
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| 1.0631 | 0.22 | 600 | 1.0911 |
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| 1.0714 | 0.26 | 700 | 1.0773 |
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| 1.0505 | 0.29 | 800 | 1.0667 |
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| 1.0475 | 0.33 | 900 | 1.0562 |
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| 1.0411 | 0.37 | 1000 | 1.0485 |
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| 1.0418 | 0.4 | 1100 | 1.0413 |
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| 1.0419 | 0.44 | 1200 | 1.0339 |
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| 1.0315 | 0.48 | 1300 | 1.0290 |
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| 1.0235 | 0.51 | 1400 | 1.0238 |
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| 1.0308 | 0.55 | 1500 | 1.0189 |
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| 1.0039 | 0.59 | 1600 | 1.0157 |
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| 1.0048 | 0.62 | 1700 | 1.0110 |
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| 0.9982 | 0.66 | 1800 | 1.0080 |
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| 1.0196 | 0.7 | 1900 | 1.0049 |
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| 1.019 | 0.73 | 2000 | 1.0030 |
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| 1.0037 | 0.77 | 2100 | 1.0009 |
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| 1.0003 | 0.81 | 2200 | 0.9995 |
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| 0.9942 | 0.84 | 2300 | 0.9982 |
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| 0.9986 | 0.88 | 2400 | 0.9974 |
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| 0.9987 | 0.92 | 2500 | 0.9969 |
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| 0.9763 | 0.95 | 2600 | 0.9967 |
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| 0.9733 | 0.99 | 2700 | 0.9967 |
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### Framework versions
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- Transformers 4.28.0.dev0
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- Pytorch 2.0.0+cu117
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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