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annavtkn
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ru_sentiment_classification_model

Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
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annavtkn commited on
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End of training

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  1. README.md +16 -14
  2. runs/Apr23_10-56-45_04d97cc2fe29/events.out.tfevents.1713869806.04d97cc2fe29.432.0 +2 -2
README.md CHANGED
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  ---
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  license: mit
 
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  tags:
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  - generated_from_trainer
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- base_model: r1char9/rubert-base-cased-russian-sentiment
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  metrics:
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  - accuracy
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  - precision
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [r1char9/rubert-base-cased-russian-sentiment](https://huggingface.co/r1char9/rubert-base-cased-russian-sentiment) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1448
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- - Accuracy: 0.7567
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- - Precision: 0.7592
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- - Recall: 0.7567
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- - F1: 0.7577
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  ## Model description
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@@ -49,20 +49,22 @@ The following hyperparameters were used during training:
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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: 3.0
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 0.6928 | 1.0 | 1250 | 0.6545 | 0.6996 | 0.7060 | 0.6996 | 0.6684 |
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- | 0.4374 | 2.0 | 2500 | 0.6781 | 0.7438 | 0.7390 | 0.7438 | 0.7361 |
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- | 0.2586 | 3.0 | 3750 | 1.1448 | 0.7567 | 0.7592 | 0.7567 | 0.7577 |
 
 
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  ### Framework versions
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- - Transformers 4.38.2
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.19.0
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- - Tokenizers 0.15.2
 
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  ---
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  license: mit
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+ base_model: r1char9/rubert-base-cased-russian-sentiment
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  tags:
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  - generated_from_trainer
 
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  metrics:
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  - accuracy
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  - precision
 
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  This model is a fine-tuned version of [r1char9/rubert-base-cased-russian-sentiment](https://huggingface.co/r1char9/rubert-base-cased-russian-sentiment) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.7114
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+ - Accuracy: 0.7556
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+ - Precision: 0.7599
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+ - Recall: 0.7556
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+ - F1: 0.7572
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  ## Model description
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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: 5.0
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.5784 | 1.0 | 2500 | 0.6348 | 0.7398 | 0.7469 | 0.7398 | 0.7421 |
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+ | 0.4404 | 2.0 | 5000 | 0.7082 | 0.7671 | 0.7636 | 0.7671 | 0.7640 |
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+ | 0.3333 | 3.0 | 7500 | 1.1448 | 0.7538 | 0.7497 | 0.7538 | 0.7507 |
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+ | 0.1922 | 4.0 | 10000 | 1.4089 | 0.7594 | 0.7638 | 0.7594 | 0.7606 |
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+ | 0.0561 | 5.0 | 12500 | 1.7114 | 0.7556 | 0.7599 | 0.7556 | 0.7572 |
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  ### Framework versions
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+ - Transformers 4.40.0
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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