Initial Commit
Browse files- README.md +95 -0
- config.json +29 -0
- pytorch_model.bin +3 -0
- training_args.bin +3 -0
README.md
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---
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license: mit
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base_model: haryoaw/scenario-teacher-data-hate_speech_filipino-model-xlm-roberta-base
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tags:
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- generated_from_trainer
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datasets:
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- hate_speech_filipino
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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-from-post-finetune-div-2-data-hate_speech_filipino-model-haryoaw
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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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# scenario-non-kd-from-post-finetune-div-2-data-hate_speech_filipino-model-haryoaw
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This model is a fine-tuned version of [haryoaw/scenario-teacher-data-hate_speech_filipino-model-xlm-roberta-base](https://huggingface.co/haryoaw/scenario-teacher-data-hate_speech_filipino-model-xlm-roberta-base) on the hate_speech_filipino dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3495
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- Accuracy: 0.7779
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- F1: 0.7601
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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: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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: 6969
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| No log | 0.32 | 100 | 0.5751 | 0.7339 | 0.7510 |
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| No log | 0.64 | 200 | 0.5171 | 0.7717 | 0.7450 |
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| No log | 0.96 | 300 | 0.4969 | 0.7784 | 0.7539 |
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| No log | 1.28 | 400 | 0.5408 | 0.7819 | 0.7548 |
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| 0.4175 | 1.6 | 500 | 0.5410 | 0.7635 | 0.7597 |
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| 0.4175 | 1.92 | 600 | 0.5166 | 0.7767 | 0.7324 |
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| 0.4175 | 2.24 | 700 | 0.5823 | 0.7651 | 0.7450 |
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| 0.4175 | 2.56 | 800 | 0.5731 | 0.7672 | 0.7293 |
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| 0.4175 | 2.88 | 900 | 0.6860 | 0.7769 | 0.7458 |
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| 0.2936 | 3.19 | 1000 | 0.7409 | 0.7684 | 0.7659 |
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| 0.2936 | 3.51 | 1100 | 0.6544 | 0.7772 | 0.7487 |
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| 0.2936 | 3.83 | 1200 | 0.6719 | 0.7604 | 0.7613 |
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| 0.2936 | 4.15 | 1300 | 0.8242 | 0.7781 | 0.7471 |
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| 0.2936 | 4.47 | 1400 | 0.8741 | 0.7838 | 0.7472 |
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| 0.199 | 4.79 | 1500 | 0.7415 | 0.7755 | 0.7509 |
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| 0.199 | 5.11 | 1600 | 0.9389 | 0.7897 | 0.7615 |
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| 0.199 | 5.43 | 1700 | 0.7985 | 0.7840 | 0.7693 |
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| 0.199 | 5.75 | 1800 | 0.9223 | 0.7741 | 0.7600 |
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| 0.199 | 6.07 | 1900 | 1.0076 | 0.7727 | 0.7667 |
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| 0.1553 | 6.39 | 2000 | 0.8541 | 0.7800 | 0.7682 |
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| 0.1553 | 6.71 | 2100 | 0.9460 | 0.7810 | 0.7600 |
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| 0.1553 | 7.03 | 2200 | 1.0575 | 0.7791 | 0.7571 |
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| 0.1553 | 7.35 | 2300 | 1.0487 | 0.7687 | 0.7657 |
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| 0.1553 | 7.67 | 2400 | 0.8495 | 0.7732 | 0.7568 |
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| 0.1316 | 7.99 | 2500 | 0.9467 | 0.7812 | 0.7658 |
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| 0.1316 | 8.31 | 2600 | 1.0491 | 0.7722 | 0.7611 |
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| 0.1316 | 8.63 | 2700 | 1.0363 | 0.7691 | 0.7275 |
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| 0.1316 | 8.95 | 2800 | 0.9130 | 0.7758 | 0.7448 |
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| 0.1316 | 9.27 | 2900 | 1.4607 | 0.7717 | 0.7562 |
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| 0.1137 | 9.58 | 3000 | 1.1874 | 0.7727 | 0.7567 |
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| 0.1137 | 9.9 | 3100 | 1.1752 | 0.7836 | 0.7672 |
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| 0.1137 | 10.22 | 3200 | 1.3495 | 0.7779 | 0.7601 |
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### Framework versions
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- Transformers 4.33.3
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- Pytorch 2.0.1
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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config.json
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{
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"_name_or_path": "haryoaw/scenario-teacher-data-hate_speech_filipino-model-xlm-roberta-base",
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"architectures": [
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"XLMRobertaForSequenceClassificationKD"
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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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"initializer_range": 0.02,
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"intermediate_size": 3072,
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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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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:9ce130d4c508644c6f643879291dbc20331c72b6be0766c6ed8bb0b8153eb635
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size 942107569
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:2de72433f4c859a8d2116c4fff4b2e3a7128965f815c20446a1012c0fe6196bc
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size 4283
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