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soft-search

Text Classification
Transformers
PyTorch
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Model card Files
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update model card README.md

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README.md CHANGED
@@ -3,7 +3,10 @@ license: apache-2.0
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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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  model-index:
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  - name: soft-search
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  results: []
@@ -16,8 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2610
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- - Accuracy: 0.8333
 
 
 
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  ## Model description
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@@ -46,18 +52,18 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 3 | 0.8268 | 0.75 |
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- | No log | 2.0 | 6 | 0.3217 | 0.8333 |
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- | No log | 3.0 | 9 | 0.2988 | 0.8333 |
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- | 0.6789 | 4.0 | 12 | 0.2457 | 0.9167 |
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- | 0.6789 | 5.0 | 15 | 0.2610 | 0.8333 |
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  ### Framework versions
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- - Transformers 4.21.1
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- - Pytorch 1.12.0+cu102
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- - Datasets 2.4.0
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- - Tokenizers 0.12.1
 
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  tags:
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  - generated_from_trainer
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  metrics:
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+ - f1
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  - accuracy
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+ - precision
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+ - recall
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  model-index:
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  - name: soft-search
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  results: []
 
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  This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7833
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+ - F1: 0.5304
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+ - Accuracy: 0.6780
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+ - Precision: 0.5333
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+ - Recall: 0.5275
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
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+ | 0.5776 | 1.0 | 50 | 0.6066 | 0.3803 | 0.6667 | 0.5294 | 0.2967 |
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+ | 0.5545 | 2.0 | 100 | 0.6261 | 0.4331 | 0.6629 | 0.5152 | 0.3736 |
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+ | 0.4599 | 3.0 | 150 | 0.7046 | 0.5472 | 0.6364 | 0.4793 | 0.6374 |
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+ | 0.2527 | 4.0 | 200 | 0.7285 | 0.5521 | 0.6742 | 0.5248 | 0.5824 |
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+ | 0.2423 | 5.0 | 250 | 0.7833 | 0.5304 | 0.6780 | 0.5333 | 0.5275 |
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  ### Framework versions
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+ - Transformers 4.24.0
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+ - Pytorch 1.13.0+cu117
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+ - Datasets 2.3.2
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+ - Tokenizers 0.13.2