LazzeKappa
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End of training
Browse files- README.md +70 -0
- config.json +59 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +13 -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: distilbert-base-multilingual-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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- accuracy
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model-index:
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- name: BERT_B07
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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_B07
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This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2269
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- Precision: 0.6290
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- Recall: 0.6789
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- F1: 0.6530
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- Accuracy: 0.9317
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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: 4e-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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.4974 | 1.0 | 46 | 0.3685 | 0.5057 | 0.4568 | 0.4800 | 0.8932 |
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| 0.2353 | 2.0 | 92 | 0.2460 | 0.5996 | 0.6272 | 0.6130 | 0.9252 |
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| 0.17 | 3.0 | 138 | 0.2264 | 0.5949 | 0.6421 | 0.6176 | 0.9286 |
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| 0.1429 | 4.0 | 184 | 0.2272 | 0.6083 | 0.6720 | 0.6386 | 0.9305 |
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| 0.1252 | 5.0 | 230 | 0.2269 | 0.6290 | 0.6789 | 0.6530 | 0.9317 |
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### Framework versions
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- Transformers 4.33.3
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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config.json
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{
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"_name_or_path": "distilbert-base-multilingual-cased",
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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": "O",
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"1": "B-Organisation",
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"2": "I-Organisation",
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"3": "B-Person",
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"4": "I-Person",
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"5": "B-Location",
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"6": "I-Location",
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"7": "B-Money",
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"8": "I-Money",
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"9": "B-Temporal",
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"10": "I-Temporal",
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"11": "B-Weapon",
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"12": "I-Weapon",
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"13": "B-MilitaryPlatform",
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"14": "I-MilitaryPlatform"
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},
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"initializer_range": 0.02,
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"label2id": {
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"B-Location": 5,
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"B-MilitaryPlatform": 13,
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"B-Money": 7,
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"B-Organisation": 1,
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"B-Person": 3,
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"B-Temporal": 9,
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"B-Weapon": 11,
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"I-Location": 6,
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"I-MilitaryPlatform": 14,
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"I-Money": 8,
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"I-Organisation": 2,
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"I-Person": 4,
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"I-Temporal": 10,
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"I-Weapon": 12,
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"O": 0
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},
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"max_position_embeddings": 512,
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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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"output_past": true,
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"pad_token_id": 0,
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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": "4.33.3",
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"vocab_size": 119547
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:7e49c6ddb52851a073d02c8da8ccb828d75aaf4fdad4b0a3c47a374f87614776
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size 539017317
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special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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tokenizer.json
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tokenizer_config.json
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{
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": false,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "DistilBertTokenizer",
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"unk_token": "[UNK]"
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:3274ec9185601881a6c124fcdd33b286f4d9636e329790eb624549b479a76d36
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size 3963
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vocab.txt
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