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med-flan-t5-large

Text2Text Generation
Transformers
PyTorch
TensorBoard
Spanish
t5
simplification
Generated from Trainer
Inference Endpoints
text-generation-inference
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bradleyfowler123 joheras commited on
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Duplicate from CLARA-MeD/flan-t5-large

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Co-authored-by: Jónathan <joheras@users.noreply.huggingface.co>

Files changed (26) hide show
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  4. config.json +32 -0
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - simplification
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+ - generated_from_trainer
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+ metrics:
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+ - rouge
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+ - sari
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+ model-index:
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+ - name: flan-t5-large-clara-med
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+ results: []
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+ datasets:
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+ - lcampillos/CLARA-MeD
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+ language:
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+ - es
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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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+ # flan-t5-large-clara-med
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+
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+ This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the [CLARA-MeD](https://huggingface.co/lcampillos/CLARA-MeD) dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0898
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+ - Rouge1: 28.9888
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+ - Rouge2: 16.3801
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+ - Rougel: 27.4186
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+ - Rougelsum: 27.4043
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+ - sari: 39.1731
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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: 5.6e-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: 5
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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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+ | No log | 1.0 | 380 | 1.1948 | 28.2861 | 15.6461 | 26.7126 | 26.7389 |
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+ | No log | 2.0 | 760 | 1.1361 | 28.3528 | 15.8519 | 26.8151 | 26.8069 |
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+ | 1.3561 | 3.0 | 1140 | 1.1051 | 29.6216 | 16.8227 | 28.0662 | 28.0613 |
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+ | 1.3561 | 4.0 | 1520 | 1.0915 | 29.3603 | 16.5008 | 27.7915 | 27.7761 |
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+ | 1.0939 | 5.0 | 1900 | 1.0898 | 28.9888 | 16.3801 | 27.4186 | 27.4043 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.25.1
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+ - Pytorch 1.13.0
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+ - Datasets 2.8.0
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+ - Tokenizers 0.12.1
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+ "architectures": [
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+ "d_kv": 64,
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+ "decoder_start_token_id": 0,
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+ "dropout_rate": 0.1,
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+ "feed_forward_proj": "gated-gelu",
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+ "initializer_factor": 1.0,
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+ "is_encoder_decoder": true,
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+ "is_gated_act": true,
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+ "layer_norm_epsilon": 1e-06,
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+ "model_type": "t5",
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+ "n_positions": 512,
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+ "num_decoder_layers": 24,
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+ "num_heads": 16,
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+ "num_layers": 24,
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+ "output_past": true,
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+ "pad_token_id": 0,
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+ "relative_attention_max_distance": 128,
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+ "relative_attention_num_buckets": 32,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.25.1",
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+ "use_cache": true,
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+ "vocab_size": 32128
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+ }
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