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pile-t5-base-ins-no_robots

Text2Text Generation
Transformers
TensorBoard
Safetensors
English
umt5
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
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c2fa588
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Files changed (11) hide show
  1. README.md +64 -0
  2. added_tokens.json +102 -0
  3. config.json +34 -0
  4. generation_config.json +7 -0
  5. model.safetensors +3 -0
  6. runs/May30_02-19-00_164d86cde833/events.out.tfevents.1717035550.164d86cde833.34.0 +3 -0
  7. special_tokens_map.json +126 -0
  8. tokenizer.json +0 -0
  9. tokenizer.model +3 -0
  10. tokenizer_config.json +945 -0
  11. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ base_model: EleutherAI/pile-t5-base
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: pile-t5-base-inst
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+ results: []
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+ ---
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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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+
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+ # pile-t5-base-inst
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+
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+ This model is a fine-tuned version of [EleutherAI/pile-t5-base](https://huggingface.co/EleutherAI/pile-t5-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.5082
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+ - Rouge2 Precision: 0.2496
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+ - Rouge2 Recall: 0.1633
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+ - Rouge2 Fmeasure: 0.1786
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-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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+ - 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_steps: 50
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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+ |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
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+ | 5.8554 | 0.58 | 1500 | 3.2533 | 0.1 | 0.0744 | 0.0721 |
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+ | 4.2403 | 1.16 | 3000 | 2.7020 | 0.1704 | 0.1174 | 0.1248 |
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+ | 3.8091 | 1.74 | 4500 | 2.5844 | 0.2476 | 0.1617 | 0.1767 |
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+ | 3.6589 | 2.32 | 6000 | 2.5289 | 0.2467 | 0.1621 | 0.1769 |
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+ | 3.5802 | 2.9 | 7500 | 2.5082 | 0.2496 | 0.1633 | 0.1786 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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