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gpt2_stereoset_finetuned

Text Classification
Transformers
PyTorch
gpt2
Generated from Trainer
Eval Results
text-generation-inference
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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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+ datasets:
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+ - stereoset
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: gpt2_stereoset_finetuned
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: stereoset
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+ type: stereoset
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+ config: intersentence
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+ split: validation
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+ args: intersentence
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.7087912087912088
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+ ---
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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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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # gpt2_stereoset_finetuned
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+
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+ This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the stereoset dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6545
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+ - Accuracy: 0.7088
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 128
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+ - eval_batch_size: 64
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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: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.21 | 5 | 1.1855 | 0.5259 |
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+ | No log | 0.42 | 10 | 0.7056 | 0.5338 |
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+ | No log | 0.62 | 15 | 0.7009 | 0.5400 |
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+ | No log | 0.83 | 20 | 0.7230 | 0.5173 |
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+ | No log | 1.04 | 25 | 0.6666 | 0.5989 |
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+ | No log | 1.25 | 30 | 0.6812 | 0.5699 |
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+ | No log | 1.46 | 35 | 0.6479 | 0.6272 |
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+ | No log | 1.67 | 40 | 0.6323 | 0.6484 |
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+ | No log | 1.88 | 45 | 0.6306 | 0.6515 |
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+ | No log | 2.08 | 50 | 0.6474 | 0.6633 |
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+ | No log | 2.29 | 55 | 0.6158 | 0.6641 |
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+ | No log | 2.5 | 60 | 0.6059 | 0.6703 |
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+ | No log | 2.71 | 65 | 0.6151 | 0.6695 |
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+ | No log | 2.92 | 70 | 0.5860 | 0.6782 |
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+ | No log | 3.12 | 75 | 0.5808 | 0.6907 |
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+ | No log | 3.33 | 80 | 0.5953 | 0.6915 |
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+ | No log | 3.54 | 85 | 0.5860 | 0.6994 |
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+ | No log | 3.75 | 90 | 0.5918 | 0.6947 |
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+ | No log | 3.96 | 95 | 0.5915 | 0.6797 |
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+ | No log | 4.17 | 100 | 0.5779 | 0.7041 |
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+ | No log | 4.38 | 105 | 0.5902 | 0.7151 |
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+ | No log | 4.58 | 110 | 0.5740 | 0.7080 |
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+ | No log | 4.79 | 115 | 0.5640 | 0.7088 |
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+ | No log | 5.0 | 120 | 0.5786 | 0.6947 |
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+ | No log | 5.21 | 125 | 0.5892 | 0.6978 |
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+ | No log | 5.42 | 130 | 0.5722 | 0.7096 |
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+ | No log | 5.62 | 135 | 0.5743 | 0.7064 |
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+ | No log | 5.83 | 140 | 0.5873 | 0.7057 |
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+ | No log | 6.04 | 145 | 0.5915 | 0.7033 |
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+ | No log | 6.25 | 150 | 0.5978 | 0.7009 |
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+ | No log | 6.46 | 155 | 0.6034 | 0.6931 |
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+ | No log | 6.67 | 160 | 0.5908 | 0.7111 |
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+ | No log | 6.88 | 165 | 0.5954 | 0.6947 |
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+ | No log | 7.08 | 170 | 0.5882 | 0.7033 |
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+ | No log | 7.29 | 175 | 0.5895 | 0.7151 |
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+ | No log | 7.5 | 180 | 0.6077 | 0.7104 |
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+ | No log | 7.71 | 185 | 0.6121 | 0.7151 |
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+ | No log | 7.92 | 190 | 0.6086 | 0.7151 |
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+ | No log | 8.12 | 195 | 0.6182 | 0.7127 |
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+ | No log | 8.33 | 200 | 0.6412 | 0.7072 |
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+ | No log | 8.54 | 205 | 0.6425 | 0.7049 |
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+ | No log | 8.75 | 210 | 0.6369 | 0.7135 |
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+ | No log | 8.96 | 215 | 0.6405 | 0.7111 |
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+ | No log | 9.17 | 220 | 0.6431 | 0.7135 |
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+ | No log | 9.38 | 225 | 0.6474 | 0.7127 |
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+ | No log | 9.58 | 230 | 0.6595 | 0.7041 |
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+ | No log | 9.79 | 235 | 0.6580 | 0.7041 |
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+ | No log | 10.0 | 240 | 0.6545 | 0.7088 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Pytorch 1.13.1
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+ - Datasets 2.9.0
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+ - Tokenizers 0.13.2