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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: distilbert-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - fin
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: distilbert-base-uncased-finetuned-ner
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: fin
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+ type: fin
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+ config: fin
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+ split: validation
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+ args: fin
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.9288256227758007
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+ - name: Recall
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+ type: recall
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+ value: 0.9354838709677419
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+ - name: F1
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+ type: f1
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+ value: 0.9321428571428573
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9919932574799831
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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-finetuned-ner
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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 fin dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0485
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+ - Precision: 0.9288
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+ - Recall: 0.9355
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+ - F1: 0.9321
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+ - Accuracy: 0.9920
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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: 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 | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 64 | 0.0876 | 0.7519 | 0.6953 | 0.7225 | 0.9768 |
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+ | No log | 2.0 | 128 | 0.0536 | 0.9091 | 0.8602 | 0.8840 | 0.9869 |
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+ | No log | 3.0 | 192 | 0.0485 | 0.9288 | 0.9355 | 0.9321 | 0.9920 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.1
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
config.json ADDED
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+ {
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+ "_name_or_path": "distilbert-base-uncased",
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+ "activation": "gelu",
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+ "architectures": [
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+ "DistilBertForTokenClassification"
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+ ],
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+ "attention_dropout": 0.1,
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+ "dim": 768,
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+ "dropout": 0.1,
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+ "hidden_dim": 3072,
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+ "id2label": {
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+ "0": "LABEL_0",
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+ "n_layers": 6,
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+ "pad_token_id": 0,
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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": "4.34.1",
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+ "vocab_size": 30522
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+ }
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tokenizer.json ADDED
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tokenizer_config.json ADDED
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