jjglilleberg
commited on
Training completed!
Browse files- README.md +14 -31
- config.json +1 -1
- model.safetensors +3 -0
- sentencepiece.bpe.model +3 -0
- tokenizer.json +2 -2
- tokenizer_config.json +44 -10
- training_args.bin +2 -2
README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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datasets:
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- xtreme
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metrics:
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- f1
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model-index:
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- name: xlm-roberta-base-finetuned-panx-fr
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results:
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- task:
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name: Token Classification
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type: token-classification
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dataset:
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name: xtreme
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type: xtreme
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config: PAN-X.fr
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split: train
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args: PAN-X.fr
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metrics:
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- name: F1
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type: f1
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value: 0.8366320026836633
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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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# xlm-roberta-base-finetuned-panx-fr
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- F1: 0.
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## Model description
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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:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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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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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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### Framework versions
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- Transformers 4.
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- Pytorch
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- Datasets 2.
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- Tokenizers 0.
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---
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license: mit
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base_model: xlm-roberta-base
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tags:
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- generated_from_trainer
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metrics:
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- f1
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model-index:
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- name: xlm-roberta-base-finetuned-panx-fr
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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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# xlm-roberta-base-finetuned-panx-fr
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2750
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- F1: 0.8495
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## Model description
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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: 24
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- eval_batch_size: 24
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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 | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 0.5647 | 1.0 | 191 | 0.3242 | 0.7728 |
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| 0.2671 | 2.0 | 382 | 0.2672 | 0.8202 |
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| 0.1744 | 3.0 | 573 | 0.2750 | 0.8495 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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config.json
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.38.2",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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model.safetensors
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size 1109860880
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sentencepiece.bpe.model
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tokenizer.json
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tokenizer_config.json
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{
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"bos_token": "<s>",
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"cls_token": "<s>",
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"eos_token": "</s>",
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"mask_token":
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"__type": "AddedToken",
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"content": "<mask>",
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"lstrip": true,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"model_max_length": 512,
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"name_or_path": "xlm-roberta-base",
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"special_tokens_map_file": null,
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"tokenizer_class": "XLMRobertaTokenizer",
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"unk_token": "<unk>"
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}
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{
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"added_tokens_decoder": {
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"0": {
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"rstrip": false,
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"single_word": false,
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"special": true
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"2": {
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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"3": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"250001": {
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"lstrip": true,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"bos_token": "<s>",
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"clean_up_tokenization_spaces": true,
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"cls_token": "<s>",
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"eos_token": "</s>",
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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": "</s>",
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"tokenizer_class": "XLMRobertaTokenizer",
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"unk_token": "<unk>"
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}
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training_args.bin
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