Training in progress, step 500
Browse files- README.md +66 -0
- config.json +36 -0
- model.safetensors +3 -0
- runs/May14_07-01-44_a99a388f55b4/events.out.tfevents.1715670105.a99a388f55b4.334.0 +3 -0
- runs/May14_07-16-06_a99a388f55b4/events.out.tfevents.1715670975.a99a388f55b4.334.1 +3 -0
- runs/May14_07-23-36_a99a388f55b4/events.out.tfevents.1715671417.a99a388f55b4.6563.0 +3 -0
- runs/May14_07-27-51_a99a388f55b4/events.out.tfevents.1715671688.a99a388f55b4.6563.1 +3 -0
- runs/May14_07-32-18_a99a388f55b4/events.out.tfevents.1715671939.a99a388f55b4.6563.2 +3 -0
- runs/May14_07-37-06_a99a388f55b4/events.out.tfevents.1715672239.a99a388f55b4.6563.3 +3 -0
- runs/May14_07-39-51_a99a388f55b4/events.out.tfevents.1715672392.a99a388f55b4.6563.4 +3 -0
- runs/May14_07-43-01_a99a388f55b4/events.out.tfevents.1715672601.a99a388f55b4.6563.5 +3 -0
- runs/May14_07-45-47_a99a388f55b4/events.out.tfevents.1715672749.a99a388f55b4.6563.6 +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +55 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
README.md
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---
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license: apache-2.0
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base_model: bert-base-cased
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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model-index:
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- name: BERT-ukpolitics
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results: []
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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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# BERT-ukpolitics
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1227
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- Precision: 0.6648
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- Recall: 0.6365
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- F1: 0.6503
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 4
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
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| No log | 1.0 | 306 | 0.0992 | 0.6679 | 0.5021 | 0.5732 |
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| 0.1045 | 2.0 | 612 | 0.1061 | 0.6347 | 0.6269 | 0.6308 |
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| 0.1045 | 3.0 | 918 | 0.1227 | 0.6648 | 0.6365 | 0.6503 |
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "bert-base-cased",
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"architectures": [
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"BertForTokenClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "O",
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"1": "I-S",
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"2": "B-S"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"B-S": 2,
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"I-S": 1,
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"O": 0
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},
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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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"torch_dtype": "float32",
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"transformers_version": "4.40.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 28996
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}
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model.safetensors
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special_tokens_map.json
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{
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tokenizer.json
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tokenizer_config.json
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training_args.bin
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vocab.txt
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