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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: distilbert-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: distilbert-base-uncased-wordnet_combined_one-fine-tuned
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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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+ # distilbert-base-uncased-wordnet_combined_one-fine-tuned
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0616
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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: 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: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 0.1841 | 1.0 | 7354 | 0.1334 |
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+ | 0.1306 | 2.0 | 14708 | 0.0756 |
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+ | 0.091 | 3.0 | 22062 | 0.0616 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.1
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+ - Pytorch 2.4.0
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.0
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+ "architectures": [
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+ "DistilBertForSequenceClassification"
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+ ],
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+ "attention_dropout": 0.1,
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+ "dropout": 0.1,
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+ "hidden_dim": 3072,
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+ "model_type": "distilbert",
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+ "n_heads": 12,
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+ "n_layers": 6,
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+ "pad_token_id": 0,
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+ "problem_type": "single_label_classification",
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+ "qa_dropout": 0.1,
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+ "seq_classif_dropout": 0.2,
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+ "sinusoidal_pos_embds": false,
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+ "tie_weights_": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.45.1",
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+ "vocab_size": 30522
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+ }
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