fine-tune-berta-TNR-split-headline1
Browse files- README.md +63 -0
- config.json +42 -0
- model.safetensors +3 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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base_model: bert-base-multilingual-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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model-index:
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- name: fine-tune-berta-TNR-split-headline1
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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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# fine-tune-berta-TNR-split-headline1
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-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: 1.0587
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- Accuracy: 0.4737
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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: 32
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- eval_batch_size: 64
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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: 7
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.081 | 1.0 | 5 | 1.0624 | 0.4737 |
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| 1.0833 | 2.0 | 10 | 1.0596 | 0.4737 |
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| 1.0903 | 3.0 | 15 | 1.0605 | 0.4737 |
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| 1.0672 | 4.0 | 20 | 1.0587 | 0.4737 |
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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-multilingual-cased",
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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": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2"
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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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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2
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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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"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": "single_label_classification",
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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": 119547
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ce5662747a20652aad2370c1b929d419f3342a7a0cc11946632604f17510d267
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size 711446532
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:1b4631cd69559f958a4e2532576e87e12086813d87a7bbedd6f8ffc9857c916d
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size 4984
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