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--- |
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license: apache-2.0 |
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base_model: DatPySci/pythia-1b-sft-full |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: pythia-1b-kto-iter0-epoch1 |
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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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# pythia-1b-kto-iter0-epoch1 |
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This model is a fine-tuned version of [DatPySci/pythia-1b-sft-full](https://huggingface.co/DatPySci/pythia-1b-sft-full) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3355 |
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- Rewards/real: -0.0044 |
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- Rewards/generated: -1.1080 |
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- Rewards/accuracies: 0.9600 |
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- Rewards/margins: 1.1036 |
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- Logps/generated: -571.6245 |
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- Logps/real: -468.8171 |
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- Logits/generated: 0.2235 |
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- Logits/real: -0.2848 |
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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-07 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 8 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 8 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/real | Rewards/generated | Rewards/accuracies | Rewards/margins | Logps/generated | Logps/real | Logits/generated | Logits/real | |
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|:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------------:|:------------------:|:---------------:|:---------------:|:----------:|:----------------:|:-----------:| |
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| 0.4016 | 0.38 | 300 | 0.3914 | 0.0270 | -0.8143 | 0.9320 | 0.8413 | -568.6872 | -468.5030 | 0.2573 | -0.2517 | |
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| 0.3451 | 0.77 | 600 | 0.3355 | -0.0044 | -1.1080 | 0.9600 | 1.1036 | -571.6245 | -468.8171 | 0.2235 | -0.2848 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.2.1 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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