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Duplicate from autoevaluate/summarization

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Co-authored-by: Lewis Tunstall <lewtun@users.noreply.huggingface.co>

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+ checkpoint-*/
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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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+ - summarization
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+ datasets:
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+ - xsum
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+ - autoevaluate/xsum-sample
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: summarization
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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: xsum
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+ type: xsum
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+ args: default
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+ metrics:
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+ - name: Rouge1
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+ type: rouge
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+ value: 23.9405
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+ duplicated_from: autoevaluate/summarization
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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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+ # summarization
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+
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+ This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.6690
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+ - Rouge1: 23.9405
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+ - Rouge2: 5.0879
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+ - Rougel: 18.4981
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+ - Rougelsum: 18.5032
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+ - Gen Len: 18.7376
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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: 16
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+ - eval_batch_size: 16
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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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+ - training_steps: 1000
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+ - mixed_precision_training: Native AMP
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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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+ | 2.9249 | 0.08 | 1000 | 2.6690 | 23.9405 | 5.0879 | 18.4981 | 18.5032 | 18.7376 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.19.2
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+ - Pytorch 1.11.0+cu113
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+ - Datasets 2.2.2
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+ - Tokenizers 0.12.1
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+ "_name_or_path": "t5-small",
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+ "architectures": [
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+ "T5ForConditionalGeneration"
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+ ],
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+ "d_ff": 2048,
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+ "d_kv": 64,
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+ "d_model": 512,
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+ "decoder_start_token_id": 0,
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+ "feed_forward_proj": "relu",
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+ "initializer_factor": 1.0,
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+ "is_encoder_decoder": 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": 6,
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+ "num_heads": 8,
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+ "num_layers": 6,
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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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+ "task_specific_params": {
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+ "summarization": {
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+ "early_stopping": true,
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+ "prefix": "summarize: "
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+ },
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+ "translation_en_to_de": {
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+ "early_stopping": true,
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+ "max_length": 300,
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+ "num_beams": 4,
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+ "prefix": "translate English to German: "
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+ "transformers_version": "4.19.2",
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+ "use_cache": true,
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+ "vocab_size": 32128
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