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scenario-NON-KD-SCR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_alpha

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: xlm-roberta-base
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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-SCR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_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-NON-KD-SCR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_alpha
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+
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+ This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 6.4834
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+ - Accuracy: 0.3758
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+ - F1: 0.3692
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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: 1123
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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 | 1.1269 | 0.3302 | 0.2264 |
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+ | 1.0552 | 2.17 | 500 | 1.4862 | 0.3673 | 0.3240 |
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+ | 1.0552 | 3.26 | 750 | 2.0425 | 0.3580 | 0.3105 |
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+ | 0.4849 | 4.35 | 1000 | 2.7827 | 0.3673 | 0.3562 |
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+ | 0.4849 | 5.43 | 1250 | 2.3787 | 0.3804 | 0.3790 |
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+ | 0.1731 | 6.52 | 1500 | 3.5404 | 0.3873 | 0.3523 |
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+ | 0.1731 | 7.61 | 1750 | 4.1335 | 0.3765 | 0.3561 |
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+ | 0.0878 | 8.7 | 2000 | 4.4114 | 0.375 | 0.3748 |
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+ | 0.0878 | 9.78 | 2250 | 4.9951 | 0.3650 | 0.3587 |
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+ | 0.036 | 10.87 | 2500 | 5.1386 | 0.3642 | 0.3569 |
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+ | 0.036 | 11.96 | 2750 | 5.4524 | 0.3711 | 0.3499 |
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+ | 0.0297 | 13.04 | 3000 | 5.4964 | 0.3681 | 0.3565 |
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+ | 0.0297 | 14.13 | 3250 | 5.3291 | 0.3765 | 0.3709 |
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+ | 0.0225 | 15.22 | 3500 | 5.6184 | 0.3719 | 0.3346 |
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+ | 0.0225 | 16.3 | 3750 | 5.4079 | 0.3719 | 0.3466 |
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+ | 0.0144 | 17.39 | 4000 | 5.6999 | 0.3634 | 0.3538 |
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+ | 0.0144 | 18.48 | 4250 | 5.7290 | 0.3681 | 0.3575 |
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+ | 0.007 | 19.57 | 4500 | 5.9349 | 0.3673 | 0.3272 |
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+ | 0.007 | 20.65 | 4750 | 5.7265 | 0.3789 | 0.3760 |
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+ | 0.0064 | 21.74 | 5000 | 6.1464 | 0.3611 | 0.3370 |
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+ | 0.0064 | 22.83 | 5250 | 6.1483 | 0.3765 | 0.3678 |
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+ | 0.0026 | 23.91 | 5500 | 6.3733 | 0.3742 | 0.3688 |
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+ | 0.0026 | 25.0 | 5750 | 6.3795 | 0.3704 | 0.3498 |
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+ | 0.002 | 26.09 | 6000 | 6.4692 | 0.3735 | 0.3582 |
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+ | 0.002 | 27.17 | 6250 | 6.5994 | 0.3727 | 0.3448 |
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+ | 0.0006 | 28.26 | 6500 | 6.4658 | 0.3758 | 0.3693 |
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+ | 0.0006 | 29.35 | 6750 | 6.4834 | 0.3758 | 0.3692 |
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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": "xlm-roberta-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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+ "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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+ "2": "LABEL_2"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "LABEL_0": 0,
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+ "LABEL_1": 1,
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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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