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bwahyuh
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gemash

Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
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  1. README.md +12 -12
  2. model.safetensors +1 -1
README.md CHANGED
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  ---
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- license: mit
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- base_model: indolem/indobert-base-uncased
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -18,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # gemash
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- This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8077
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- - Accuracy: 0.7517
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- - Precision: 0.7645
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- - Recall: 0.7614
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- - F1: 0.7619
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 1.5073 | 1.0 | 169 | 1.3572 | 0.43 | 0.4010 | 0.3978 | 0.3732 |
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- | 1.1536 | 2.0 | 338 | 1.0170 | 0.6083 | 0.6592 | 0.5946 | 0.5925 |
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- | 0.7413 | 3.0 | 507 | 0.8618 | 0.7183 | 0.7324 | 0.7277 | 0.7269 |
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- | 0.446 | 4.0 | 676 | 0.8077 | 0.7517 | 0.7645 | 0.7614 | 0.7619 |
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  ### Framework versions
 
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  ---
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+ license: apache-2.0
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+ base_model: indolem/indobertweet-base-uncased
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # gemash
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+ This model is a fine-tuned version of [indolem/indobertweet-base-uncased](https://huggingface.co/indolem/indobertweet-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9414
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+ - Accuracy: 0.8033
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+ - Precision: 0.8149
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+ - Recall: 0.8086
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+ - F1: 0.8116
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 1.2534 | 1.0 | 169 | 0.9392 | 0.6333 | 0.6682 | 0.6642 | 0.6550 |
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+ | 0.6263 | 2.0 | 338 | 0.7132 | 0.7767 | 0.8099 | 0.7776 | 0.7901 |
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+ | 0.194 | 3.0 | 507 | 0.8639 | 0.7883 | 0.7911 | 0.8039 | 0.7961 |
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+ | 0.0485 | 4.0 | 676 | 0.9414 | 0.8033 | 0.8149 | 0.8086 | 0.8116 |
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  ### Framework versions
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