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--- |
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library_name: peft |
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base_model: mjschock/TinyLlama-1.1B-Chat-v1.0 |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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metrics: |
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- bleu |
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- rouge |
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model-index: |
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- name: TinyLlama-1.1B-Chat-v1.0-sft-chat_threads |
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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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# TinyLlama-1.1B-Chat-v1.0-sft-chat_threads |
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This model is a fine-tuned version of [mjschock/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/mjschock/TinyLlama-1.1B-Chat-v1.0) on the mjschock/chat_threads dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5586 |
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- Bleu: 0.7572 |
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- Precisions: 0.7641 |
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- Brevity Penalty: 0.9983 |
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- Length Ratio: 0.9986 |
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- Translation Length: 582.3552 |
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- Reference Length: 582.9104 |
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- Meteor: 0.7364 |
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- Rouge1: 0.7900 |
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- Rouge2: 0.5570 |
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- Rougel: 0.7250 |
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- Rougelsum: 0.7838 |
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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: 5e-05 |
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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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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Meteor | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:----------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|:------:|:------:|:---------:| |
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| No log | 0 | 0 | 0.8976 | 0.6391 | 0.6567 | 0.9934 | 0.9936 | 579.7720 | 582.9104 | 0.6775 | 0.6912 | 0.3881 | 0.5809 | 0.6813 | |
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| 0.7612 | 0.9630 | 13 | 0.7168 | 0.6941 | 0.7056 | 0.9969 | 0.9973 | 581.2681 | 582.9104 | 0.7030 | 0.7375 | 0.4604 | 0.6572 | 0.7281 | |
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| 0.6321 | 2.0 | 27 | 0.5992 | 0.7420 | 0.7498 | 0.9981 | 0.9981 | 582.0161 | 582.9104 | 0.7312 | 0.7780 | 0.5342 | 0.7069 | 0.7720 | |
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| 0.5738 | 2.8889 | 39 | 0.5586 | 0.7572 | 0.7641 | 0.9983 | 0.9986 | 582.3552 | 582.9104 | 0.7364 | 0.7900 | 0.5570 | 0.7250 | 0.7838 | |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.44.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.19.1 |
