End of training
Browse files- README.md +76 -0
- pytorch_model.bin +1 -1
README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- emotion
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metrics:
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- accuracy
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model-index:
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- name: sagemaker-distilbert-emotion-1
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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: emotion
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type: emotion
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9325
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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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# sagemaker-distilbert-emotion-1
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1651
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- Accuracy: 0.9325
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 32
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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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- lr_scheduler_warmup_steps: 500
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- num_epochs: 3
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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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| 0.966 | 1.0 | 500 | 0.2497 | 0.921 |
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| 0.1913 | 2.0 | 1000 | 0.1651 | 0.9325 |
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| 0.1037 | 3.0 | 1500 | 0.1501 | 0.9285 |
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### Framework versions
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- Transformers 4.12.3
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- Pytorch 1.9.1
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- Datasets 1.15.1
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- Tokenizers 0.10.3
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pytorch_model.bin
CHANGED
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 267872369
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version https://git-lfs.github.com/spec/v1
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size 267872369
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