hajili/xlm-roberta-large-azsci-topics
Browse files- .gitattributes +1 -0
- README.md +70 -0
- config.json +79 -0
- model.safetensors +3 -0
- runs/Mar03_10-55-48_ec070931aaa2/events.out.tfevents.1709463354.ec070931aaa2.108733.0 +3 -0
- sentencepiece.bpe.model +3 -0
- special_tokens_map.json +15 -0
- tokenizer.json +3 -0
- tokenizer_config.json +54 -0
- training_args.bin +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: mit
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base_model: FacebookAI/xlm-roberta-large
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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: xlm-roberta-large-azsci-topics
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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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# xlm-roberta-large-azsci-topics
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4012
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- Precision: 0.9115
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- Recall: 0.9158
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- F1: 0.9121
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- Accuracy: 0.9158
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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: 16
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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: 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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| No log | 1.0 | 288 | 0.6402 | 0.8063 | 0.8073 | 0.7900 | 0.8073 |
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| 1.0792 | 2.0 | 576 | 0.4482 | 0.8827 | 0.8776 | 0.8743 | 0.8776 |
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| 1.0792 | 3.0 | 864 | 0.3947 | 0.8968 | 0.9019 | 0.8977 | 0.9019 |
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| 0.3135 | 4.0 | 1152 | 0.4177 | 0.9043 | 0.9080 | 0.9047 | 0.9080 |
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| 0.3135 | 5.0 | 1440 | 0.4012 | 0.9115 | 0.9158 | 0.9121 | 0.9158 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.1.0+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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{
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"_name_or_path": "FacebookAI/xlm-roberta-large",
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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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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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"0": "LABEL_0",
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "xlm-roberta",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"output_past": true,
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"pad_token_id": 1,
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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": "4.38.2",
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"use_cache": true,
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"vocab_size": 250002
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}
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model.safetensors
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runs/Mar03_10-55-48_ec070931aaa2/events.out.tfevents.1709463354.ec070931aaa2.108733.0
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sentencepiece.bpe.model
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version https://git-lfs.github.com/spec/v1
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special_tokens_map.json
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{
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}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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tokenizer_config.json
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 4920
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