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bart-base-finetuned-tldrhq-cnn-dailymail

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  1. README.md +61 -0
  2. config.json +75 -0
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  40. merges.txt +0 -0
  41. special_tokens_map.json +1 -0
  42. tf_model.h5 +3 -0
  43. tokenizer.json +0 -0
  44. tokenizer_config.json +1 -0
  45. vocab.json +0 -0
README.md ADDED
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+ ---
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+ tags:
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+ - generated_from_keras_callback
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+ model-index:
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+ - name: Prototypeu/bart-base-finetuned-tldrhq-cnn-dailymail
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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 Keras had access to. You should
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+ probably proofread and complete it, then remove this comment. -->
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+
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+ # Prototypeu/bart-base-finetuned-tldrhq-cnn-dailymail
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+
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+ This model is a fine-tuned version of [Prototypeu/bart-base-finetuned-xsum](https://huggingface.co/Prototypeu/bart-base-finetuned-xsum) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Train Loss: 1.5049
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+ - Train Logits Loss: 1.5049
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+ - Train Rouge1: 28.1795
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+ - Train Rouge2: 14.0392
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+ - Train Rougel: 23.7617
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+ - Train Rougelsum: 26.5583
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+ - Train Gen Len: 19.0
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+ - Epoch: 4
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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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+ - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 3e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 255113, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 32000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.98, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
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+ - training_precision: float32
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+
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+ ### Training results
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+
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+ | Train Loss | Train Logits Loss | Train Rouge1 | Train Rouge2 | Train Rougel | Train Rougelsum | Train Gen Len | Epoch |
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+ |:----------:|:-----------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:|
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+ | 2.9074 | 2.9074 | 26.9164 | 12.6984 | 22.4321 | 25.2287 | 19.0 | 0 |
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+ | 1.9368 | 1.9368 | 28.0165 | 13.8906 | 23.4187 | 26.3779 | 19.0 | 1 |
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+ | 1.7246 | 1.7246 | 27.6022 | 13.5255 | 23.2301 | 25.9923 | 19.0 | 2 |
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+ | 1.5945 | 1.5945 | 28.0347 | 13.7045 | 23.4851 | 26.3488 | 19.0 | 3 |
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+ | 1.5049 | 1.5049 | 28.1795 | 14.0392 | 23.7617 | 26.5583 | 19.0 | 4 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.17.0
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+ - TensorFlow 2.6.0
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+ - Datasets 2.0.0
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+ - Tokenizers 0.11.6
config.json ADDED
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+ {
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+ "_name_or_path": "Prototypeu/bart-base-finetuned-xsum",
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+ "activation_dropout": 0.1,
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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": 0.1,
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+ "bos_token_id": 0,
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+ "classif_dropout": 0.1,
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+ "classifier_dropout": 0.0,
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+ "d_model": 768,
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+ "decoder_attention_heads": 12,
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+ "decoder_ffn_dim": 3072,
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+ "decoder_layerdrop": 0.0,
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+ "decoder_layers": 6,
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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": 12,
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+ "encoder_ffn_dim": 3072,
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+ "encoder_layerdrop": 0.0,
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+ "encoder_layers": 6,
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+ "eos_token_id": 2,
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+ "forced_bos_token_id": 0,
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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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+ "1": "LABEL_1",
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+ "2": "LABEL_2"
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+ },
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+ "init_std": 0.02,
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+ "is_encoder_decoder": true,
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+ "label2id": {
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+ "LABEL_0": 0,
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+ "LABEL_1": 1,
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+ "LABEL_2": 2
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+ },
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+ "max_position_embeddings": 1024,
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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": 4,
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+ "num_hidden_layers": 6,
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+ "pad_token_id": 1,
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+ "scale_embedding": false,
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+ "task_specific_params": {
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+ "summarization": {
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+ "length_penalty": 1.0,
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+ "max_length": 128,
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+ "min_length": 12,
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+ "num_beams": 4
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+ },
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+ "summarization_cnn": {
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+ "length_penalty": 2.0,
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+ "max_length": 142,
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+ "min_length": 56,
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+ "num_beams": 4
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+ },
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+ "summarization_xsum": {
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+ "length_penalty": 1.0,
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+ "max_length": 62,
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+ "min_length": 11,
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+ "num_beams": 6
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+ }
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+ },
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.17.0",
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+ "use_cache": true,
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+ "vocab_size": 50265
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+ }
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