Training in progress, epoch 1

README.md

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+---
+base_model: csebuetnlp/banglabert
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: banglabert-MLTC-BB
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# banglabert-MLTC-BB
+
+This model is a fine-tuned version of [csebuetnlp/banglabert](https://huggingface.co/csebuetnlp/banglabert) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3730
+- F1: 0.8628
+- Roc Auc: 0.8612
+- Accuracy: 0.5784
+- Hamming Loss: 0.1388
+- Jaccard Score: 0.7587
+- Zero One Loss: 0.4216
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy | Hamming Loss | Jaccard Score | Zero One Loss |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:------------:|:-------------:|:-------------:|
+| 0.4126        | 1.0   | 146  | 0.4229          | 0.8333 | 0.8303  | 0.5527   | 0.1697       | 0.7143        | 0.4473        |
+| 0.381         | 2.0   | 292  | 0.3605          | 0.8551 | 0.8541  | 0.5835   | 0.1459       | 0.7469        | 0.4165        |
+| 0.2885        | 3.0   | 438  | 0.3745          | 0.8589 | 0.8521  | 0.5656   | 0.1478       | 0.7527        | 0.4344        |
+| 0.2324        | 4.0   | 584  | 0.3612          | 0.8597 | 0.8579  | 0.5835   | 0.1420       | 0.7539        | 0.4165        |
+| 0.2618        | 5.0   | 730  | 0.3458          | 0.8632 | 0.8631  | 0.5861   | 0.1369       | 0.7593        | 0.4139        |
+| 0.2535        | 6.0   | 876  | 0.3673          | 0.8611 | 0.8579  | 0.5758   | 0.1420       | 0.7561        | 0.4242        |
+| 0.1701        | 7.0   | 1022 | 0.3932          | 0.8559 | 0.8528  | 0.5681   | 0.1472       | 0.7481        | 0.4319        |
+| 0.1835        | 8.0   | 1168 | 0.3641          | 0.8668 | 0.8650  | 0.5887   | 0.1350       | 0.7648        | 0.4113        |
+| 0.1714        | 9.0   | 1314 | 0.3796          | 0.8617 | 0.8605  | 0.5707   | 0.1395       | 0.7570        | 0.4293        |
+| 0.1311        | 10.0  | 1460 | 0.3730          | 0.8628 | 0.8612  | 0.5784   | 0.1388       | 0.7587        | 0.4216        |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.1.2
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "csebuetnlp/banglabert",
+  "architectures": [
+    "ElectraForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "embedding_size": 768,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Personal Attack",
+    "1": "Sexism",
+    "2": "Racism",
+    "3": "hate speech"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Personal Attack": 0,
+    "Racism": 2,
+    "Sexism": 1,
+    "hate speech": 3
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "electra",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "multi_label_classification",
+  "summary_activation": "gelu",
+  "summary_last_dropout": 0.1,
+  "summary_type": "first",
+  "summary_use_proj": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 32000
+}

model.safetensors

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+size 442505824

special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
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+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "single_word": false,
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+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": false,
+  "full_tokenizer_file": null,
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": false,
+  "tokenizer_class": "ElectraTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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