sivan22 commited on
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End of training

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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: dicta-il/BEREL_2.0
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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: my_awesome_model
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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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+ # my_awesome_model
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+
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+ This model is a fine-tuned version of [dicta-il/BEREL_2.0](https://huggingface.co/dicta-il/BEREL_2.0) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1927
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+ - Accuracy: 0.9507
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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: 2
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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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+ | 0.2694 | 1.0 | 537 | 0.1761 | 0.9409 |
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+ | 0.0922 | 2.0 | 1074 | 0.1927 | 0.9507 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0
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+ - Pytorch 2.0.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.13.3
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+ "BertForSequenceClassification"
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+ "gradient_checkpointing": false,
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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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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "rabbinic": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.33.0",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 128000
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+ }
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