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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: t5-base
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - bigbench
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: bigbench_entailedpolarity-t5-base
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: bigbench
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+ type: bigbench
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+ config: entailed_polarity
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+ split: train
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+ args: entailed_polarity
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9583333333333334
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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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+ # bigbench_entailedpolarity-t5-base
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+
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+ This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the bigbench dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3881
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+ - Accuracy: 0.9583
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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: 5e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 32
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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: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 24 | 0.4860 | 0.875 |
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+ | No log | 2.0 | 48 | 0.3200 | 0.875 |
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+ | No log | 3.0 | 72 | 0.3107 | 0.9167 |
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+ | No log | 4.0 | 96 | 0.3666 | 0.9167 |
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+ | No log | 5.0 | 120 | 0.5273 | 0.9167 |
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+ | No log | 6.0 | 144 | 0.3190 | 0.9583 |
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+ | No log | 7.0 | 168 | 0.3328 | 0.9583 |
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+ | No log | 8.0 | 192 | 0.5994 | 0.9167 |
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+ | No log | 9.0 | 216 | 0.6515 | 0.9167 |
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+ | No log | 10.0 | 240 | 0.6435 | 0.9167 |
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+ | No log | 11.0 | 264 | 0.6450 | 0.9167 |
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+ | No log | 12.0 | 288 | 0.6565 | 0.9167 |
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+ | No log | 13.0 | 312 | 0.6484 | 0.9167 |
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+ | No log | 14.0 | 336 | 0.6376 | 0.9167 |
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+ | No log | 15.0 | 360 | 0.6808 | 0.9167 |
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+ | No log | 16.0 | 384 | 0.6884 | 0.9167 |
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+ | No log | 17.0 | 408 | 0.6502 | 0.9167 |
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+ | No log | 18.0 | 432 | 0.6781 | 0.9167 |
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+ | No log | 19.0 | 456 | 0.3894 | 0.9583 |
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+ | No log | 20.0 | 480 | 0.3881 | 0.9583 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 1.10.1+cu102
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
config.json ADDED
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+ {
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+ "_name_or_path": "t5-base",
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+ "architectures": [
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+ "T5ForSequenceClassification"
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+ ],
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+ "classifier_dropout": 0.0,
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+ "d_ff": 3072,
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+ "d_kv": 64,
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+ "d_model": 768,
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+ "decoder_start_token_id": 0,
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+ "dense_act_fn": "relu",
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+ "dropout_rate": 0.1,
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+ "eos_token_id": 1,
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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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+ "is_gated_act": false,
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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": 12,
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+ "num_heads": 12,
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+ "num_layers": 12,
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+ "output_past": true,
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+ "pad_token_id": 0,
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+ "problem_type": "single_label_classification",
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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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+ },
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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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+ },
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+ "translation_en_to_fr": {
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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 French: "
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+ },
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+ "translation_en_to_ro": {
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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 Romanian: "
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+ }
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+ },
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.2",
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+ "use_cache": true,
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+ "vocab_size": 32128
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+ }
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