End of training
Browse files- .gitattributes +1 -0
- README.md +34 -6
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- training_args.bin +1 -1
.gitattributes
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README.md
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- generated_from_trainer
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datasets:
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- glue
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model-index:
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- name: bert_uncased_L-6_H-768_A-12-QAT
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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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# bert_uncased_L-6_H-768_A-12-QAT
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This model is a fine-tuned version of [google/bert_uncased_L-6_H-768_A-12](https://huggingface.co/google/bert_uncased_L-6_H-768_A-12) on the glue dataset.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size:
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- eval_batch_size:
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- seed:
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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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### Framework versions
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- generated_from_trainer
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datasets:
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- glue
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metrics:
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- accuracy
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model-index:
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- name: bert_uncased_L-6_H-768_A-12-QAT
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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: glue
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type: glue
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config: sst2
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split: validation
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args: sst2
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8176605504587156
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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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# bert_uncased_L-6_H-768_A-12-QAT
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This model is a fine-tuned version of [google/bert_uncased_L-6_H-768_A-12](https://huggingface.co/google/bert_uncased_L-6_H-768_A-12) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7339
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- Accuracy: 0.8177
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 6e-05
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- train_batch_size: 128
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- eval_batch_size: 128
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- seed: 33
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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: 7
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- mixed_precision_training: Native AMP
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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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| 0.3055 | 1.0 | 8 | 0.4989 | 0.8303 |
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| 0.192 | 2.0 | 16 | 0.4659 | 0.8108 |
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| 0.0994 | 3.0 | 24 | 0.5389 | 0.8177 |
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| 0.0324 | 4.0 | 32 | 0.7313 | 0.8096 |
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| 0.0164 | 5.0 | 40 | 0.6689 | 0.8211 |
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| 0.0137 | 6.0 | 48 | 0.7148 | 0.8154 |
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| 0.0041 | 7.0 | 56 | 0.7339 | 0.8177 |
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### Framework versions
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nncf_output.log
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if `fn` has an unbound 0-th `self` argument, or
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with model.nncf.temporary_bound_original_forward(fn): ...
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if `fn` already had 0-th `self` argument bound or never had it in the first place.
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if `fn` has an unbound 0-th `self` argument, or
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with model.nncf.temporary_bound_original_forward(fn): ...
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if `fn` already had 0-th `self` argument bound or never had it in the first place.
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WARNING:nncf:You are setting `forward` on an NNCF-processed model object.
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NNCF relies on custom-wrapping the `forward` call in order to function properly.
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Arbitrary adjustments to the forward function on an NNCFNetwork object have undefined behavior.
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If you need to replace the underlying forward function of the original model so that NNCF should be using that instead of the original forward function that NNCF saved during the compressed model creation, you can do this by calling:
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model.nncf.set_original_unbound_forward(fn)
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if `fn` has an unbound 0-th `self` argument, or
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with model.nncf.temporary_bound_original_forward(fn): ...
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if `fn` already had 0-th `self` argument bound or never had it in the first place.
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WARNING:nncf:You are setting `forward` on an NNCF-processed model object.
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NNCF relies on custom-wrapping the `forward` call in order to function properly.
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Arbitrary adjustments to the forward function on an NNCFNetwork object have undefined behavior.
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If you need to replace the underlying forward function of the original model so that NNCF should be using that instead of the original forward function that NNCF saved during the compressed model creation, you can do this by calling:
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model.nncf.set_original_unbound_forward(fn)
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if `fn` has an unbound 0-th `self` argument, or
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with model.nncf.temporary_bound_original_forward(fn): ...
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if `fn` already had 0-th `self` argument bound or never had it in the first place.
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