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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-xsum
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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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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: conversation-summ
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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: samsum
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+ type: samsum
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+ config: samsum
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+ split: validation
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+ args: samsum
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+ metrics:
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+ - name: Rouge1
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+ type: rouge
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+ value: 54.5508
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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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+ # conversation-summ
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+
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+ This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the samsum dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3072
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+ - Rouge1: 54.5508
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+ - Rouge2: 29.5843
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+ - Rougel: 44.5124
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+ - Rougelsum: 50.0064
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+ - Gen Len: 30.1968
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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: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 4
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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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
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+ | 0.2898 | 1.0 | 3683 | 0.3072 | 54.5508 | 29.5843 | 44.5124 | 50.0064 | 30.1968 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0
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+ - Pytorch 2.0.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.13.3
config.json ADDED
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+ {
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+ "_name_or_path": "facebook/bart-large-xsum",
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+ "_num_labels": 3,
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+ "activation_dropout": 0.0,
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+ "activation_function": "gelu",
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+ "add_bias_logits": false,
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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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+ "classif_dropout": 0.0,
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+ "classifier_dropout": 0.0,
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+ "d_model": 1024,
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+ "decoder_attention_heads": 16,
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+ "decoder_ffn_dim": 4096,
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+ "decoder_layerdrop": 0.0,
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+ "decoder_layers": 12,
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+ "decoder_start_token_id": 2,
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+ "dropout": 0.1,
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+ "early_stopping": true,
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+ "encoder_attention_heads": 16,
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+ "encoder_layerdrop": 0.0,
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+ "eos_token_id": 2,
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+ "eos_token_ids": [
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+ 2
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+ ],
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+ "forced_eos_token_id": 2,
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+ "gradient_checkpointing": false,
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+ "id2label": {
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+ "0": "LABEL_0",
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+ "max_length": 62,
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+ "min_length": 11,
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+ "model_type": "bart",
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+ "no_repeat_ngram_size": 3,
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+ "normalize_before": false,
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+ "normalize_embedding": true,
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+ "num_beams": 6,
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+ "num_hidden_layers": 12,
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+ "output_past": true,
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+ "prefix": " ",
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+ "replacing_rate": 0,
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+ "scale_embedding": false,
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+ "static_position_embeddings": false,
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+ "student_decoder_layers": null,
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+ "student_encoder_layers": null,
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+ "task_specific_params": {},
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.33.0",
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+ "use_cache": true,
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+ "vocab_size": 50264
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+ }
generation_config.json ADDED
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