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gpt2-sentiment_analysis

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  1. README.md +14 -15
  2. adapter_model.safetensors +1 -1
  3. runs/May27_03-29-08_313da2eeec49/events.out.tfevents.1716780560.313da2eeec49.741.0 +3 -0
  4. runs/May27_03-29-08_313da2eeec49/events.out.tfevents.1716780817.313da2eeec49.741.1 +3 -0
  5. runs/May27_03-37-38_313da2eeec49/events.out.tfevents.1716781070.313da2eeec49.6635.0 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -11,7 +11,6 @@ metrics:
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  model-index:
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  - name: gpt2-sentiment_analysis
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  results: []
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- pipeline_tag: text-classification
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -21,8 +20,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the financial_phrasebank dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7017
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- - Accuracy: {'accuracy': 0.8941548183254344}
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  ## Model description
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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 | 224 | 0.4513 | {'accuracy': 0.8515007898894155} |
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- | No log | 2.0 | 448 | 0.3301 | {'accuracy': 0.8862559241706162} |
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- | 0.2776 | 3.0 | 672 | 0.3686 | {'accuracy': 0.8862559241706162} |
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- | 0.2776 | 4.0 | 896 | 0.3920 | {'accuracy': 0.8767772511848341} |
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- | 0.198 | 5.0 | 1120 | 0.3815 | {'accuracy': 0.8925750394944708} |
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- | 0.198 | 6.0 | 1344 | 0.5228 | {'accuracy': 0.8720379146919431} |
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- | 0.1346 | 7.0 | 1568 | 0.5616 | {'accuracy': 0.8846761453396524} |
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- | 0.1346 | 8.0 | 1792 | 0.5480 | {'accuracy': 0.9020537124802528} |
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- | 0.0823 | 9.0 | 2016 | 0.6681 | {'accuracy': 0.8957345971563981} |
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- | 0.0823 | 10.0 | 2240 | 0.7017 | {'accuracy': 0.8941548183254344} |
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  ### Framework versions
 
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  model-index:
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  - name: gpt2-sentiment_analysis
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  results: []
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the financial_phrasebank dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6571
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+ - Accuracy: {'accuracy': 0.8239339752407153}
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  ## Model description
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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 | 0.9981 | 257 | 0.4654 | {'accuracy': 0.8239339752407153} |
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+ | 0.6288 | 2.0 | 515 | 0.4266 | {'accuracy': 0.8266850068775791} |
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+ | 0.6288 | 2.9981 | 772 | 0.4558 | {'accuracy': 0.8225584594222833} |
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+ | 0.3201 | 4.0 | 1030 | 0.4550 | {'accuracy': 0.811554332874828} |
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+ | 0.3201 | 4.9981 | 1287 | 0.4223 | {'accuracy': 0.8294360385144429} |
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+ | 0.2464 | 6.0 | 1545 | 0.4637 | {'accuracy': 0.8335625859697386} |
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+ | 0.2464 | 6.9981 | 1802 | 0.5243 | {'accuracy': 0.8184319119669876} |
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+ | 0.1859 | 8.0 | 2060 | 0.5482 | {'accuracy': 0.8335625859697386} |
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+ | 0.1859 | 8.9981 | 2317 | 0.6443 | {'accuracy': 0.8335625859697386} |
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+ | 0.1381 | 9.9806 | 2570 | 0.6571 | {'accuracy': 0.8239339752407153} |
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  ### Framework versions
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