End of training
Browse files- README.md +71 -0
- config.json +106 -0
- logs/events.out.tfevents.1718452370.1f9650542848.648.0 +3 -0
- logs/events.out.tfevents.1718455960.1f9650542848.648.1 +3 -0
- model.safetensors +3 -0
- training_args.bin +3 -0
README.md
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---
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base_model: FPTAI/vibert-base-cased
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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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- f1
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model-index:
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- name: vibert-base-cased-ed
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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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# vibert-base-cased-ed
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This model is a fine-tuned version of [FPTAI/vibert-base-cased](https://huggingface.co/FPTAI/vibert-base-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0595
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- F1 Micro: 0.7034
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- F1 Macro: 0.0430
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- Accuracy: 0.6374
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- Recall Micro: 0.6094
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- Precision Micro: 0.8317
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- Recall Macro: 0.0392
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- Precision Macro: 0.0621
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- F1: 0.5913
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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: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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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 | F1 Micro | F1 Macro | Accuracy | Recall Micro | Precision Micro | Recall Macro | Precision Macro | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:------------:|:---------------:|:------------:|:---------------:|:------:|
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| 0.0696 | 1.0 | 1526 | 0.0711 | 0.6892 | 0.0243 | 0.7054 | 0.6737 | 0.7054 | 0.0294 | 0.0207 | 0.5573 |
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| 0.055 | 2.0 | 3052 | 0.0622 | 0.6965 | 0.0252 | 0.6345 | 0.6060 | 0.8187 | 0.0265 | 0.0241 | 0.5775 |
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| 0.0631 | 3.0 | 4578 | 0.0598 | 0.7054 | 0.0255 | 0.6436 | 0.6147 | 0.8274 | 0.0268 | 0.0243 | 0.5847 |
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| 0.0534 | 4.0 | 6104 | 0.0591 | 0.6980 | 0.0260 | 0.6268 | 0.5989 | 0.8362 | 0.0265 | 0.0540 | 0.5809 |
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| 0.0296 | 5.0 | 7630 | 0.0595 | 0.7034 | 0.0430 | 0.6374 | 0.6094 | 0.8317 | 0.0392 | 0.0621 | 0.5913 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.20.0
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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": "FPTAI/vibert-base-cased",
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"_num_labels": 2,
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"architectures": [
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"BertForSequenceClassification"
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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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"directionality": "bidi",
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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": "Appeal",
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"1": "Merge-org",
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"2": "Sue",
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"3": "O",
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"4": "End-position",
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"5": "Start-position",
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"6": "Transfer-ownership",
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"7": "Sentence",
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"8": "Transfer-money",
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"9": "Trial-hearing",
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"10": "Die",
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"11": "Injure",
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"12": "Release-parole",
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"13": "Divorce",
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"14": "Marry",
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"15": "Pardon",
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"16": "Meet",
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"17": "Convict",
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"18": "Demonstrate",
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"19": "Start-org",
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"20": "Extradite",
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"21": "Fine",
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"22": "Execute",
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"23": "Phone-write",
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"24": "Arrest-jail",
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"25": "End-org",
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"26": "Elect",
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"27": "Declare-bankruptcy",
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"28": "Nominate",
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"29": "Attack",
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"30": "Be-born",
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"31": "Arquit",
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"32": "Transport",
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"33": "Charge-indict"
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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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"Appeal": 0,
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"Arquit": 31,
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"Arrest-jail": 24,
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"Attack": 29,
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"Be-born": 30,
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"Charge-indict": 33,
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"Convict": 17,
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"Declare-bankruptcy": 27,
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"Demonstrate": 18,
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"Die": 10,
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"Divorce": 13,
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"Elect": 26,
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"End-org": 25,
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"End-position": 4,
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"Execute": 22,
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"Extradite": 20,
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"Fine": 21,
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"Injure": 11,
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"Marry": 14,
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"Meet": 16,
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"Merge-org": 1,
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"Nominate": 28,
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"O": 3,
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"Pardon": 15,
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"Phone-write": 23,
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"Release-parole": 12,
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"Sentence": 7,
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"Start-org": 19,
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"Start-position": 5,
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"Sue": 2,
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"Transfer-money": 8,
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"Transfer-ownership": 6,
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"Transport": 32,
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"Trial-hearing": 9
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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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"output_past": true,
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"pad_token_id": 0,
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"pooler_fc_size": 768,
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"pooler_num_attention_heads": 12,
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"pooler_num_fc_layers": 3,
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"pooler_size_per_head": 128,
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"pooler_type": "first_token_transform",
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"position_embedding_type": "absolute",
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"problem_type": "multi_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.41.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 38168
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}
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logs/events.out.tfevents.1718452370.1f9650542848.648.0
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version https://git-lfs.github.com/spec/v1
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size 171283
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logs/events.out.tfevents.1718455960.1f9650542848.648.1
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version https://git-lfs.github.com/spec/v1
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size 791
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 461545600
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 5112
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