End of training
Browse files- README.md +12 -10
- config.json +1 -1
- pytorch_model.bin +1 -1
- training_args.bin +1 -1
README.md
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---
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license: apache-2.0
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base_model:
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tags:
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- generated_from_trainer
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model-index:
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@@ -13,9 +13,9 @@ should probably proofread and complete it, then remove this comment. -->
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# bert-mini-hangman
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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- Loss:
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size:
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- eval_batch_size:
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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:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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### Framework versions
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- Transformers 4.33.2
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- Pytorch 2.0.1
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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---
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license: apache-2.0
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base_model: vaibhav9/bert-mini-hangman
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tags:
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- generated_from_trainer
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model-index:
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# bert-mini-hangman
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This model is a fine-tuned version of [vaibhav9/bert-mini-hangman](https://huggingface.co/vaibhav9/bert-mini-hangman) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: nan
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 1.5549 | 1.0 | 2609 | nan |
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| 1.5426 | 2.0 | 5218 | nan |
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| 1.5294 | 3.0 | 7827 | nan |
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| 1.5251 | 4.0 | 10436 | nan |
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| 1.5043 | 5.0 | 13045 | nan |
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### Framework versions
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- Transformers 4.33.2
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- Pytorch 2.0.1
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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config.json
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{
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"_name_or_path": "
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"architectures": [
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"BertForMaskedLM"
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],
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{
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"_name_or_path": "vaibhav9/bert-mini-hangman",
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"architectures": [
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"BertForMaskedLM"
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],
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pytorch_model.bin
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training_args.bin
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