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README.md
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---
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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-65b-en-pt-es-ca
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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-65b-en-pt-es-ca
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This model was trained from scratch on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7271
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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: 1
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- gradient_accumulation_steps: 63
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- total_train_batch_size: 126
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- total_eval_batch_size: 2
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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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| 0.8069 | 0.06 | 100 | 0.8033 |
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| 0.8008 | 0.13 | 200 | 0.7826 |
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| 0.7687 | 0.19 | 300 | 0.7721 |
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| 0.7719 | 0.25 | 400 | 0.7647 |
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| 0.7585 | 0.32 | 500 | 0.7588 |
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| 0.7578 | 0.38 | 600 | 0.7537 |
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| 0.7505 | 0.44 | 700 | 0.7491 |
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| 0.7531 | 0.51 | 800 | 0.7449 |
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| 0.7394 | 0.57 | 900 | 0.7416 |
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| 0.7368 | 0.63 | 1000 | 0.7387 |
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| 0.7412 | 0.69 | 1100 | 0.7361 |
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| 0.7344 | 0.76 | 1200 | 0.7288 |
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| 0.7383 | 0.82 | 1300 | 0.7281 |
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| 0.7378 | 0.88 | 1400 | 0.7274 |
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| 0.7204 | 0.95 | 1500 | 0.7271 |
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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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