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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- Fraser/short-jokes |
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metrics: |
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- accuracy |
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model-index: |
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- name: pythia-1.4b-deduped-jokes |
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results: |
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- task: |
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name: Causal Language Modeling |
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type: text-generation |
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dataset: |
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name: Fraser/short-jokes |
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type: Fraser/short-jokes |
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config: default |
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split: train[:5%] |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.986989308918276 |
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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-1.4b-deduped-jokes |
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This model is a fine-tuned version of [EleutherAI/pythia-1.4b-deduped](https://huggingface.co/EleutherAI/pythia-1.4b-deduped) on the Fraser/short-jokes dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0699 |
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- Accuracy: 0.9870 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 32 |
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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: 0.05 |
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- training_steps: 400 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 0.06 | 100 | 0.0729 | 0.9866 | |
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| No log | 0.12 | 200 | 0.0716 | 0.9868 | |
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| No log | 0.17 | 300 | 0.0705 | 0.9869 | |
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| No log | 0.23 | 400 | 0.0699 | 0.9870 | |
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### Framework versions |
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- Transformers 4.29.0.dev0 |
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- Pytorch 2.0.0-rc1 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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