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your_username/bert-emotion

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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: bert-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: summerschool-2layer-copa
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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 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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+ # summerschool-2layer-copa
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8767
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+ - Accuracy: 0.7015
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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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+ - 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 | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.6792 | 0.2793 | 50 | 0.6678 | 0.5759 |
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+ | 0.6489 | 0.5587 | 100 | 0.6514 | 0.6147 |
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+ | 0.6282 | 0.8380 | 150 | 0.6360 | 0.6461 |
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+ | 0.5746 | 1.1173 | 200 | 0.6596 | 0.6492 |
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+ | 0.5325 | 1.3966 | 250 | 0.6253 | 0.6785 |
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+ | 0.5431 | 1.6760 | 300 | 0.6226 | 0.6712 |
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+ | 0.5058 | 1.9553 | 350 | 0.5896 | 0.6869 |
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+ | 0.3982 | 2.2346 | 400 | 0.6467 | 0.6859 |
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+ | 0.3837 | 2.5140 | 450 | 0.7012 | 0.6785 |
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+ | 0.3714 | 2.7933 | 500 | 0.7326 | 0.6586 |
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+ | 0.347 | 3.0726 | 550 | 0.7592 | 0.6702 |
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+ | 0.247 | 3.3520 | 600 | 0.7466 | 0.6942 |
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+ | 0.2382 | 3.6313 | 650 | 0.7514 | 0.6953 |
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+ | 0.2304 | 3.9106 | 700 | 0.8268 | 0.6838 |
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+ | 0.1716 | 4.1899 | 750 | 0.8822 | 0.6806 |
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+ | 0.1631 | 4.4693 | 800 | 0.8698 | 0.6932 |
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+ | 0.1435 | 4.7486 | 850 | 0.9178 | 0.6838 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
config.json ADDED
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+ {
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+ "_name_or_path": "bert-base-uncased",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.41.2",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30522
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+ }
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