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neuropark
/
sahajBERT-NCC

Text Classification
Transformers
PyTorch
Bengali
albert
collaborative
bengali
SequenceClassification
Inference Endpoints
Model card Files Community
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Step 19519

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Files changed (3) hide show
  1. README.md +12 -12
  2. config.json +2 -2
  3. pytorch_model.bin +1 -1
README.md CHANGED
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  ## Training data
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- The model was initialized with pre-trained weights of [sahajBERT](https://huggingface.co/neuropark/sahajBERT) at step 19169 and trained on the `sna.bn` split of [IndicGlue](https://huggingface.co/datasets/indic_glue).
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  ## Training procedure
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  ## Eval results
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- accuracy: 0.9192062367115521
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- loss: 0.2882556915283203
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- macro_f1: 0.8987860792763027
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- macro_precision: 0.9047413783524961
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- macro_recall: 0.8938654072561182
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- micro_f1: 0.919206236711552
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- micro_precision: 0.9192062367115521
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- micro_recall: 0.9192062367115521
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- weighted_f1: 0.9190050640322454
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- weighted_precision: 0.9191484504954501
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- weighted_recall: 0.9192062367115521
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  ## Training data
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+ The model was initialized with pre-trained weights of [sahajBERT](https://huggingface.co/neuropark/sahajBERT) at step 19519 and trained on the `sna.bn` split of [IndicGlue](https://huggingface.co/datasets/indic_glue).
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  ## Training procedure
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  ## Eval results
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+ accuracy: 0.9163713678242381
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+ loss: 0.29771897196769714
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+ macro_f1: 0.8951960933373831
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+ macro_precision: 0.8958313840463195
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+ macro_recall: 0.8962088356299692
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+ micro_f1: 0.9163713678242381
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+ micro_precision: 0.9163713678242381
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+ micro_recall: 0.9163713678242381
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+ weighted_f1: 0.916670480049282
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+ weighted_precision: 0.9180146709071523
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+ weighted_recall: 0.9163713678242381
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config.json CHANGED
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  {
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- "_name_or_path": "albertvillanova/autonlp-indic_glue-multi_class_classification-0d675eb-1291121",
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  "_num_labels": 6,
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  "architectures": [
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  "AlbertForSequenceClassification"
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  "5": 5
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  },
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  "layer_norm_eps": 1e-12,
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- "max_length": 192,
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  "max_position_embeddings": 512,
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  "model_type": "albert",
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  "net_structure_type": 0,
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  {
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+ "_name_or_path": "albertvillanova/autonlp-indic_glue-multi_class_classification-1e67664-1311135",
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  "_num_labels": 6,
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  "architectures": [
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  "AlbertForSequenceClassification"
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  "5": 5
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  },
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  "layer_norm_eps": 1e-12,
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+ "max_length": 128,
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  "max_position_embeddings": 512,
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  "model_type": "albert",
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  "net_structure_type": 0,
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