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scenario-TCR-XLMV_data-en-cardiff_eng_only_alpha2

Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +90 -0
  2. config.json +38 -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: facebook/xlm-v-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-TCR-XLMV_data-en-cardiff_eng_only_alpha2
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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-TCR-XLMV_data-en-cardiff_eng_only_alpha2
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+
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+ This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.6119
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+ - Accuracy: 0.5472
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+ - F1: 0.5508
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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: 24
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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 | 1.03 | 60 | 1.0411 | 0.4652 | 0.4291 |
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+ | No log | 2.07 | 120 | 1.0685 | 0.5035 | 0.4475 |
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+ | No log | 3.1 | 180 | 1.1001 | 0.5485 | 0.5474 |
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+ | No log | 4.14 | 240 | 1.0647 | 0.5516 | 0.5549 |
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+ | No log | 5.17 | 300 | 1.2458 | 0.5489 | 0.5528 |
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+ | No log | 6.21 | 360 | 1.2913 | 0.5719 | 0.5717 |
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+ | No log | 7.24 | 420 | 1.5986 | 0.5437 | 0.5459 |
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+ | No log | 8.28 | 480 | 1.6908 | 0.5498 | 0.5510 |
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+ | 0.641 | 9.31 | 540 | 1.7310 | 0.5582 | 0.5587 |
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+ | 0.641 | 10.34 | 600 | 1.9959 | 0.5388 | 0.5394 |
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+ | 0.641 | 11.38 | 660 | 2.2660 | 0.5357 | 0.5401 |
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+ | 0.641 | 12.41 | 720 | 2.3724 | 0.5507 | 0.5543 |
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+ | 0.641 | 13.45 | 780 | 2.5843 | 0.5450 | 0.5464 |
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+ | 0.641 | 14.48 | 840 | 2.7003 | 0.5534 | 0.5556 |
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+ | 0.641 | 15.52 | 900 | 2.7255 | 0.5459 | 0.5491 |
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+ | 0.641 | 16.55 | 960 | 2.9127 | 0.5481 | 0.5504 |
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+ | 0.1116 | 17.59 | 1020 | 2.9543 | 0.5432 | 0.5462 |
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+ | 0.1116 | 18.62 | 1080 | 3.0564 | 0.5560 | 0.5591 |
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+ | 0.1116 | 19.66 | 1140 | 3.1501 | 0.5494 | 0.5530 |
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+ | 0.1116 | 20.69 | 1200 | 3.2882 | 0.5467 | 0.5507 |
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+ | 0.1116 | 21.72 | 1260 | 3.3562 | 0.5459 | 0.5496 |
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+ | 0.1116 | 22.76 | 1320 | 3.4030 | 0.5538 | 0.5573 |
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+ | 0.1116 | 23.79 | 1380 | 3.4897 | 0.5489 | 0.5523 |
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+ | 0.1116 | 24.83 | 1440 | 3.5540 | 0.5476 | 0.5508 |
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+ | 0.0147 | 25.86 | 1500 | 3.5772 | 0.5498 | 0.5530 |
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+ | 0.0147 | 26.9 | 1560 | 3.6123 | 0.5481 | 0.5515 |
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+ | 0.0147 | 27.93 | 1620 | 3.5954 | 0.5494 | 0.5529 |
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+ | 0.0147 | 28.97 | 1680 | 3.6081 | 0.5489 | 0.5524 |
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+ | 0.0147 | 30.0 | 1740 | 3.6119 | 0.5472 | 0.5508 |
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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": "facebook/xlm-v-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": 12,
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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": 901629
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+ }
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