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scenario-KD-PO-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_all_alpha

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PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +109 -0
  2. config.json +39 -0
  3. pytorch_model.bin +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all_a
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - tweet_sentiment_multilingual
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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-KD-PO-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_all_alpha
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+ results: []
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+ ---
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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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+
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+ # scenario-KD-PO-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_all_alpha
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+
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+ This model is a fine-tuned version of [haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all_a](https://huggingface.co/haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all_a) on the tweet_sentiment_multilingual dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.4750
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+ - Accuracy: 0.5637
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+ - F1: 0.5640
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 2222
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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: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
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+ | 4.905 | 1.09 | 500 | 4.5461 | 0.4363 | 0.4113 |
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+ | 4.0059 | 2.17 | 1000 | 3.6093 | 0.5058 | 0.5040 |
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+ | 3.4109 | 3.26 | 1500 | 3.4190 | 0.5208 | 0.5131 |
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+ | 3.0676 | 4.35 | 2000 | 3.2675 | 0.5490 | 0.5477 |
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+ | 2.7673 | 5.43 | 2500 | 3.2746 | 0.5467 | 0.5412 |
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+ | 2.5421 | 6.52 | 3000 | 3.1951 | 0.5475 | 0.5367 |
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+ | 2.3609 | 7.61 | 3500 | 3.3137 | 0.5432 | 0.5410 |
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+ | 2.1176 | 8.7 | 4000 | 3.5963 | 0.5451 | 0.5303 |
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+ | 1.9583 | 9.78 | 4500 | 3.5109 | 0.5571 | 0.5583 |
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+ | 1.8268 | 10.87 | 5000 | 3.3664 | 0.5471 | 0.5477 |
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+ | 1.7388 | 11.96 | 5500 | 3.3858 | 0.5517 | 0.5528 |
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+ | 1.5976 | 13.04 | 6000 | 3.4404 | 0.5617 | 0.5577 |
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+ | 1.4912 | 14.13 | 6500 | 3.3307 | 0.5586 | 0.5585 |
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+ | 1.4157 | 15.22 | 7000 | 3.5579 | 0.5432 | 0.5355 |
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+ | 1.3536 | 16.3 | 7500 | 3.3542 | 0.5617 | 0.5603 |
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+ | 1.2883 | 17.39 | 8000 | 3.6026 | 0.5571 | 0.5543 |
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+ | 1.2443 | 18.48 | 8500 | 3.6866 | 0.5478 | 0.5458 |
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+ | 1.1637 | 19.57 | 9000 | 3.6125 | 0.5536 | 0.5547 |
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+ | 1.1391 | 20.65 | 9500 | 3.5456 | 0.5613 | 0.5574 |
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+ | 1.1029 | 21.74 | 10000 | 3.4366 | 0.5513 | 0.5526 |
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+ | 1.0417 | 22.83 | 10500 | 3.6791 | 0.5586 | 0.5585 |
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+ | 1.0169 | 23.91 | 11000 | 3.6637 | 0.5656 | 0.5607 |
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+ | 1.0107 | 25.0 | 11500 | 3.5452 | 0.5575 | 0.5578 |
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+ | 0.9502 | 26.09 | 12000 | 3.4362 | 0.5748 | 0.5742 |
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+ | 0.9455 | 27.17 | 12500 | 3.4865 | 0.5694 | 0.5703 |
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+ | 0.9194 | 28.26 | 13000 | 3.4523 | 0.5737 | 0.5716 |
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+ | 0.9053 | 29.35 | 13500 | 3.5411 | 0.5586 | 0.5572 |
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+ | 0.8737 | 30.43 | 14000 | 3.6550 | 0.5586 | 0.5586 |
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+ | 0.865 | 31.52 | 14500 | 3.5079 | 0.5594 | 0.5611 |
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+ | 0.8444 | 32.61 | 15000 | 3.4885 | 0.5509 | 0.5526 |
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+ | 0.8343 | 33.7 | 15500 | 3.5705 | 0.5710 | 0.5698 |
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+ | 0.8122 | 34.78 | 16000 | 3.4910 | 0.5521 | 0.5519 |
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+ | 0.8161 | 35.87 | 16500 | 3.5302 | 0.5559 | 0.5563 |
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+ | 0.7923 | 36.96 | 17000 | 3.5031 | 0.5656 | 0.5632 |
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+ | 0.7824 | 38.04 | 17500 | 3.4182 | 0.5594 | 0.5592 |
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+ | 0.7658 | 39.13 | 18000 | 3.5265 | 0.5594 | 0.5586 |
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+ | 0.7588 | 40.22 | 18500 | 3.4465 | 0.5706 | 0.5711 |
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+ | 0.7541 | 41.3 | 19000 | 3.4879 | 0.5540 | 0.5534 |
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+ | 0.7488 | 42.39 | 19500 | 3.4246 | 0.5687 | 0.5693 |
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+ | 0.7412 | 43.48 | 20000 | 3.4806 | 0.5745 | 0.5750 |
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+ | 0.7314 | 44.57 | 20500 | 3.5638 | 0.5590 | 0.5586 |
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+ | 0.7283 | 45.65 | 21000 | 3.4212 | 0.5664 | 0.5667 |
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+ | 0.7179 | 46.74 | 21500 | 3.4444 | 0.5556 | 0.5560 |
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+ | 0.7168 | 47.83 | 22000 | 3.4104 | 0.5602 | 0.5606 |
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+ | 0.7161 | 48.91 | 22500 | 3.3766 | 0.5667 | 0.5676 |
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+ | 0.7052 | 50.0 | 23000 | 3.4750 | 0.5637 | 0.5640 |
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+
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+
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+ ### Framework versions
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+
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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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+ "XLMRobertaForSequenceClassificationKD"
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+ ],
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+ "id2label": {
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+ "layer_norm_eps": 1e-05,
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+ "model_type": "xlm-roberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 6,
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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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+ "use_cache": true,
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+ "vocab_size": 250002
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+ }
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