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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: google/mt5-small
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - xsum
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: ML5-fine-tuning-xsum
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+ results:
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+ - task:
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+ name: Sequence-to-sequence Language Modeling
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+ type: text2text-generation
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+ dataset:
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+ name: xsum
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+ type: xsum
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+ config: default
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+ split: test
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+ args: default
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+ metrics:
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+ - name: Rouge1
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+ type: rouge
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+ value: 0.5714
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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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+ # ML5-fine-tuning-xsum
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+
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+ This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the xsum dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 7.4333
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+ - Rouge1: 0.5714
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+ - Rouge2: 0.0
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+ - Rougel: 0.5714
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+ - Rougelsum: 0.5714
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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: 0.001
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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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+ - num_epochs: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
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+ | 18.7065 | 1.0 | 7 | 9.6966 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 10.3198 | 2.0 | 14 | 7.4333 | 0.5714 | 0.0 | 0.5714 | 0.5714 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.1
generation_config.json ADDED
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+ {
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+ "decoder_start_token_id": 0,
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+ "eos_token_id": 1,
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+ "pad_token_id": 0,
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+ "transformers_version": "4.45.2"
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+ }
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