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NasimB
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gpt2_left_out_switchboard

Text Generation
Transformers
PyTorch
gpt2
Generated from Trainer
Inference Endpoints
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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+ - generator
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+ model-index:
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+ - name: gpt2_left_out_switchboard
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+ results: []
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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_left_out_switchboard
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+
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+ This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the generator dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.9378
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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: 0.0005
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+ - train_batch_size: 64
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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: cosine
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+ - lr_scheduler_warmup_steps: 1000
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+ - num_epochs: 10
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 5.983 | 0.24 | 500 | 5.0786 |
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+ | 4.7603 | 0.48 | 1000 | 4.6865 |
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+ | 4.4521 | 0.73 | 1500 | 4.4635 |
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+ | 4.2512 | 0.97 | 2000 | 4.3124 |
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+ | 4.0458 | 1.21 | 2500 | 4.2272 |
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+ | 3.9687 | 1.45 | 3000 | 4.1443 |
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+ | 3.9024 | 1.69 | 3500 | 4.0705 |
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+ | 3.8439 | 1.93 | 4000 | 4.0057 |
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+ | 3.6791 | 2.18 | 4500 | 3.9845 |
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+ | 3.6259 | 2.42 | 5000 | 3.9471 |
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+ | 3.6137 | 2.66 | 5500 | 3.9057 |
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+ | 3.592 | 2.9 | 6000 | 3.8654 |
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+ | 3.4438 | 3.14 | 6500 | 3.8758 |
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+ | 3.3844 | 3.38 | 7000 | 3.8570 |
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+ | 3.3977 | 3.63 | 7500 | 3.8324 |
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+ | 3.4015 | 3.87 | 8000 | 3.8053 |
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+ | 3.2638 | 4.11 | 8500 | 3.8300 |
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+ | 3.1771 | 4.35 | 9000 | 3.8250 |
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+ | 3.1914 | 4.59 | 9500 | 3.8070 |
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+ | 3.1993 | 4.84 | 10000 | 3.7853 |
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+ | 3.1089 | 5.08 | 10500 | 3.8146 |
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+ | 2.9539 | 5.32 | 11000 | 3.8262 |
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+ | 2.9853 | 5.56 | 11500 | 3.8173 |
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+ | 2.9984 | 5.8 | 12000 | 3.8020 |
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+ | 2.9462 | 6.04 | 12500 | 3.8259 |
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+ | 2.7343 | 6.29 | 13000 | 3.8527 |
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+ | 2.7724 | 6.53 | 13500 | 3.8499 |
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+ | 2.7817 | 6.77 | 14000 | 3.8423 |
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+ | 2.7789 | 7.01 | 14500 | 3.8510 |
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+ | 2.5477 | 7.25 | 15000 | 3.8873 |
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+ | 2.5643 | 7.5 | 15500 | 3.8904 |
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+ | 2.5842 | 7.74 | 16000 | 3.8896 |
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+ | 2.5913 | 7.98 | 16500 | 3.8858 |
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+ | 2.4293 | 8.22 | 17000 | 3.9177 |
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+ | 2.4253 | 8.46 | 17500 | 3.9231 |
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+ | 2.4274 | 8.7 | 18000 | 3.9240 |
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+ | 2.4331 | 8.95 | 18500 | 3.9254 |
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+ | 2.362 | 9.19 | 19000 | 3.9346 |
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+ | 2.3519 | 9.43 | 19500 | 3.9373 |
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+ | 2.3498 | 9.67 | 20000 | 3.9378 |
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+ | 2.3461 | 9.91 | 20500 | 3.9378 |
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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 1.11.0+cu113
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+ - Datasets 2.13.0
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+ - Tokenizers 0.13.3