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End of training

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  1. README.md +36 -6
  2. generation_config.json +1 -2
  3. pytorch_model.bin +1 -1
README.md CHANGED
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  ---
 
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  tags:
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  - generated_from_trainer
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  datasets:
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  - govreport-summarization
 
 
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  model-index:
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  - name: led-large-16384-govreport
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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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  # led-large-16384-govreport
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- This model is a fine-tuned version of [Xmm/led-large-16384-govreport](https://huggingface.co/Xmm/led-large-16384-govreport) on the govreport-summarization dataset.
 
 
 
 
 
 
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  ## Model description
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@@ -36,15 +58,23 @@ The following hyperparameters were used during training:
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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: 8
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- - total_train_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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  - num_epochs: 5
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  ### Framework versions
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  - Transformers 4.30.2
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- - Pytorch 2.0.1+cu118
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- - Datasets 2.13.0
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  - Tokenizers 0.13.3
 
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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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  - govreport-summarization
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+ metrics:
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+ - rouge
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  model-index:
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  - name: led-large-16384-govreport
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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: govreport-summarization
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+ type: govreport-summarization
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+ config: document
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+ split: validation
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+ args: document
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+ metrics:
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+ - name: Rouge1
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+ type: rouge
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+ value: 0.5194151586540673
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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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  # led-large-16384-govreport
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+ This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the govreport-summarization dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.7624
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+ - Rouge1: 0.5194
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+ - Rouge2: 0.2107
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+ - Rougel: 0.2437
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+ - Rougelsum: 0.2437
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  ## Model description
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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: 64
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+ - total_train_batch_size: 64
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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: 5
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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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+ | 1.8152 | 3.65 | 500 | 1.7956 | 0.5095 | 0.2040 | 0.2382 | 0.2381 |
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+ | 1.6981 | 3.66 | 1000 | 1.7624 | 0.5194 | 0.2107 | 0.2437 | 0.2437 |
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+
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+
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  ### Framework versions
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  - Transformers 4.30.2
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+ - Pytorch 1.10.0+cu102
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+ - Datasets 2.13.1
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  - Tokenizers 0.13.3
generation_config.json CHANGED
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  "min_length": 100,
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  "no_repeat_ngram_size": 3,
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  "pad_token_id": 1,
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- "transformers_version": "4.30.2",
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- "use_cache": false
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  }
 
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  "min_length": 100,
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  "no_repeat_ngram_size": 3,
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  "pad_token_id": 1,
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+ "transformers_version": "4.30.2"
 
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  }
pytorch_model.bin CHANGED
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