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scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_delta

Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +88 -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-cl-cardiff_cl_only2
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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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+ - f1
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+ model-index:
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+ - name: scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_delta
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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-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_delta
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+
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+ This model is a fine-tuned version of [haryoaw/scenario-TCR_data-cl-cardiff_cl_only2](https://huggingface.co/haryoaw/scenario-TCR_data-cl-cardiff_cl_only2) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 5.5684
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+ - Accuracy: 0.4676
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+ - F1: 0.4662
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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: 11213
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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: 30
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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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+ | No log | 1.09 | 250 | 1.8346 | 0.4684 | 0.4686 |
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+ | 0.5182 | 2.17 | 500 | 2.4903 | 0.4745 | 0.4735 |
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+ | 0.5182 | 3.26 | 750 | 2.5207 | 0.4830 | 0.4775 |
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+ | 0.2149 | 4.35 | 1000 | 3.1950 | 0.4468 | 0.4376 |
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+ | 0.2149 | 5.43 | 1250 | 3.2340 | 0.4738 | 0.4669 |
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+ | 0.1358 | 6.52 | 1500 | 3.7896 | 0.4761 | 0.4750 |
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+ | 0.1358 | 7.61 | 1750 | 3.2005 | 0.4954 | 0.4933 |
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+ | 0.0968 | 8.7 | 2000 | 3.7302 | 0.4491 | 0.4429 |
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+ | 0.0968 | 9.78 | 2250 | 4.0015 | 0.4691 | 0.4662 |
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+ | 0.0624 | 10.87 | 2500 | 4.1400 | 0.4514 | 0.4462 |
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+ | 0.0624 | 11.96 | 2750 | 4.6716 | 0.4460 | 0.4388 |
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+ | 0.0508 | 13.04 | 3000 | 4.6683 | 0.4545 | 0.4531 |
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+ | 0.0508 | 14.13 | 3250 | 4.9959 | 0.4398 | 0.4311 |
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+ | 0.0408 | 15.22 | 3500 | 4.6543 | 0.4537 | 0.4541 |
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+ | 0.0408 | 16.3 | 3750 | 4.7483 | 0.4753 | 0.4765 |
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+ | 0.0272 | 17.39 | 4000 | 5.0125 | 0.4468 | 0.4446 |
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+ | 0.0272 | 18.48 | 4250 | 5.1208 | 0.4475 | 0.4438 |
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+ | 0.0241 | 19.57 | 4500 | 5.0070 | 0.4599 | 0.4586 |
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+ | 0.0241 | 20.65 | 4750 | 4.8782 | 0.4761 | 0.4759 |
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+ | 0.0187 | 21.74 | 5000 | 5.1882 | 0.4599 | 0.4608 |
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+ | 0.0187 | 22.83 | 5250 | 5.1202 | 0.4761 | 0.4761 |
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+ | 0.0086 | 23.91 | 5500 | 5.4158 | 0.4622 | 0.4616 |
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+ | 0.0086 | 25.0 | 5750 | 5.4933 | 0.4637 | 0.4620 |
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+ | 0.0088 | 26.09 | 6000 | 5.5752 | 0.4622 | 0.4604 |
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+ | 0.0088 | 27.17 | 6250 | 5.5790 | 0.4668 | 0.4648 |
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+ | 0.0063 | 28.26 | 6500 | 5.5069 | 0.4614 | 0.4603 |
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+ | 0.0063 | 29.35 | 6750 | 5.5684 | 0.4676 | 0.4662 |
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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
config.json ADDED
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+ {
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+ "_name_or_path": "haryoaw/scenario-TCR_data-cl-cardiff_cl_only2",
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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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+ "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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+ },
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+ "LABEL_2": 2
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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": 12,
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+ "num_hidden_layers": 6,
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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": "4.33.3",
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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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+ }
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