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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: facebook/bart-large-cnn
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - samsum
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+ model-index:
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+ - name: bart-cnn-samsum-finetuned
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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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+ # bart-cnn-samsum-finetuned
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+
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+ This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the samsum dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2493
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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: 1e-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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+ - num_epochs: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.113 | 1.0 | 148 | 0.2493 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.1
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
config.json ADDED
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+ "activation_dropout": 0.0,
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+ "activation_function": "gelu",
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+ "add_final_layer_norm": false,
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+ "architectures": [
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+ "BartForConditionalGeneration"
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+ ],
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 0,
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+ "dropout": 0.1,
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+ "early_stopping": true,
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+ "encoder_layerdrop": 0.0,
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+ "force_bos_token_to_be_generated": true,
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+ "gradient_checkpointing": false,
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+ "id2label": {
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+ "max_position_embeddings": 1024,
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+ "min_length": 56,
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+ "model_type": "bart",
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+ }
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.33.1",
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+ "use_cache": true,
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+ "vocab_size": 50264
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+ }
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