Initial Commit
Browse files- README.md +85 -0
- config.json +152 -0
- pytorch_model.bin +3 -0
- training_args.bin +3 -0
README.md
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---
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license: mit
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base_model: facebook/xlm-v-base
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tags:
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- generated_from_trainer
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datasets:
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- massive
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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: scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_delta2
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: massive
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type: massive
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config: all_1.1
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split: validation
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args: all_1.1
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.051647811116576486
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- name: F1
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type: f1
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value: 0.0016647904742274576
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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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# scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_delta2
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This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base) on the massive dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.8750
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- Accuracy: 0.0516
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- F1: 0.0017
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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: 32
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- eval_batch_size: 32
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- seed: 2
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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: 500
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
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| 3.7486 | 0.27 | 5000 | 3.7603 | 0.0620 | 0.0020 |
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| 3.7278 | 0.53 | 10000 | 3.8114 | 0.0620 | 0.0020 |
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| 3.7049 | 0.8 | 15000 | 3.8427 | 0.0516 | 0.0017 |
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| 3.7157 | 1.07 | 20000 | 3.8730 | 0.0516 | 0.0017 |
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| 3.7141 | 1.34 | 25000 | 3.8796 | 0.0516 | 0.0017 |
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| 3.699 | 1.6 | 30000 | 3.8750 | 0.0516 | 0.0017 |
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### Framework versions
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- Transformers 4.33.3
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- Pytorch 2.1.1+cu121
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- Datasets 2.14.5
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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": "facebook/xlm-v-base",
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"architectures": [
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"XLMRobertaForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"hidden_act": "gelu",
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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 sha256:1857a2f104325c5a44ce23dc6a65939f777aa22898c93c69c2be6b00ef9e0474
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size 3114226670
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:08b5aa268d58e7ec72405f6887f7877804fb0fa82a663a02ae87685eb822ba3d
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size 4600
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