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mBERT-B-offensive

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README.md CHANGED
@@ -1,6 +1,6 @@
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  ---
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- license: mit
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- base_model: neuralmind/bert-base-portuguese-cased
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -17,13 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # content
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- This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7314
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- - Accuracy: 0.7625
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- - F1-score: 0.7462
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- - Recall: 0.8237
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- - Precision: 0.6821
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  ## Model description
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@@ -54,19 +54,19 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Recall | Precision |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:------:|:---------:|
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- | 0.5117 | 0.3814 | 500 | 0.4886 | 0.7659 | 0.7709 | 0.8595 | 0.6988 |
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- | 0.4755 | 0.7628 | 1000 | 0.4602 | 0.7584 | 0.7561 | 0.8170 | 0.7036 |
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- | 0.4107 | 1.1442 | 1500 | 0.5348 | 0.7730 | 0.7774 | 0.8651 | 0.7059 |
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- | 0.3685 | 1.5256 | 2000 | 0.4585 | 0.7728 | 0.7755 | 0.8563 | 0.7085 |
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- | 0.3652 | 1.9069 | 2500 | 0.4497 | 0.7802 | 0.7733 | 0.8182 | 0.7331 |
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- | 0.2919 | 2.2883 | 3000 | 0.5390 | 0.7659 | 0.7561 | 0.7920 | 0.7233 |
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- | 0.2614 | 2.6697 | 3500 | 0.5387 | 0.7636 | 0.7647 | 0.8382 | 0.7030 |
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- | 0.2518 | 3.0511 | 4000 | 0.6425 | 0.7679 | 0.7411 | 0.7252 | 0.7578 |
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- | 0.1791 | 3.4325 | 4500 | 0.6974 | 0.7682 | 0.7478 | 0.7502 | 0.7455 |
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- | 0.1803 | 3.8139 | 5000 | 0.6828 | 0.7831 | 0.7744 | 0.8126 | 0.7396 |
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- | 0.1531 | 4.1953 | 5500 | 0.8737 | 0.7690 | 0.7439 | 0.7320 | 0.7561 |
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- | 0.1267 | 4.5767 | 6000 | 0.9225 | 0.7730 | 0.7555 | 0.7651 | 0.7460 |
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- | 0.1344 | 4.9580 | 6500 | 0.9057 | 0.7753 | 0.7573 | 0.7651 | 0.7497 |
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  ### Framework versions
 
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  ---
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+ license: apache-2.0
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+ base_model: google-bert/bert-base-multilingual-cased
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # content
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+ This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4643
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+ - Accuracy: 0.7959
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+ - F1-score: 0.7686
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+ - Recall: 0.8062
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+ - Precision: 0.7343
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Recall | Precision |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:------:|:---------:|
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+ | 0.5842 | 0.3814 | 500 | 0.5475 | 0.7275 | 0.7439 | 0.8704 | 0.6496 |
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+ | 0.5066 | 0.7628 | 1000 | 0.5066 | 0.7527 | 0.7544 | 0.8351 | 0.6879 |
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+ | 0.4702 | 1.1442 | 1500 | 0.5164 | 0.7524 | 0.7611 | 0.8672 | 0.6781 |
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+ | 0.4287 | 1.5256 | 2000 | 0.4908 | 0.7902 | 0.7760 | 0.7992 | 0.7542 |
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+ | 0.428 | 1.9069 | 2500 | 0.5179 | 0.7553 | 0.7643 | 0.8722 | 0.6801 |
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+ | 0.368 | 2.2883 | 3000 | 0.5774 | 0.7476 | 0.7377 | 0.7804 | 0.6994 |
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+ | 0.3507 | 2.6697 | 3500 | 0.5190 | 0.7770 | 0.7784 | 0.8609 | 0.7103 |
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+ | 0.3285 | 3.0511 | 4000 | 0.6028 | 0.7745 | 0.7684 | 0.8225 | 0.7209 |
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+ | 0.2697 | 3.4325 | 4500 | 0.5910 | 0.7725 | 0.7745 | 0.8590 | 0.7051 |
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+ | 0.2697 | 3.8139 | 5000 | 0.5870 | 0.7679 | 0.7554 | 0.7879 | 0.7254 |
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+ | 0.2274 | 4.1953 | 5500 | 0.7693 | 0.7690 | 0.7558 | 0.7860 | 0.7279 |
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+ | 0.2076 | 4.5767 | 6000 | 0.7267 | 0.7676 | 0.7535 | 0.7810 | 0.7279 |
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+ | 0.2057 | 4.9580 | 6500 | 0.7228 | 0.7653 | 0.7494 | 0.7716 | 0.7285 |
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  ### Framework versions
config.json CHANGED
@@ -1,5 +1,5 @@
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  {
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- "_name_or_path": "neuralmind/bert-base-portuguese-cased",
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  "architectures": [
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  "BertForSequenceClassification"
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  ],
@@ -16,7 +16,6 @@
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  "model_type": "bert",
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  "num_attention_heads": 12,
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  "num_hidden_layers": 12,
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- "output_past": true,
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  "pad_token_id": 0,
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  "pooler_fc_size": 768,
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  "pooler_num_attention_heads": 12,
@@ -29,5 +28,5 @@
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  "transformers_version": "4.42.4",
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  "type_vocab_size": 2,
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  "use_cache": true,
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- "vocab_size": 29794
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  }
 
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  {
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+ "_name_or_path": "google-bert/bert-base-multilingual-cased",
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  "architectures": [
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  "BertForSequenceClassification"
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  ],
 
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  "model_type": "bert",
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  "num_attention_heads": 12,
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  "num_hidden_layers": 12,
 
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  "pad_token_id": 0,
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  "pooler_fc_size": 768,
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  "pooler_num_attention_heads": 12,
 
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  "transformers_version": "4.42.4",
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  "type_vocab_size": 2,
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  "use_cache": true,
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+ "vocab_size": 119547
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  }
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tokenizer_config.json CHANGED
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  "do_basic_tokenize": true,
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