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End of training

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  3. training_args.bin +1 -1
README.md CHANGED
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  # sentiment-guesser
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- This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on the [imdb dataset](https://huggingface.co/datasets/imdb).
 
 
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- See the [colab here](https://huggingface.co/eddyjin/sentiment-guesser/blob/main/Train_a_simple_sentiment_classifier_on_Hugging_Face.ipynb).
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- This is part of [www.huggingfacetutorial.com](https://www.huggingfacetutorial.com), where you can find easy to follow tutorials on AI modeling on Hugging Face.
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  ## Intended uses & limitations
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- This model is not very good. It is only intended to be a simple example of how to fine-tune.
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  ## Training and evaluation data
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  ## Training procedure
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- Training was done on a sampled set of 1,000 examples. The eval set is also 1,000 examples. Only 1 epoch was completed to make this example easy to run on a CPU powered colab.
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-
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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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: 1
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 1.0 | 125 | 0.3983 |
 
 
 
 
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  ### Framework versions
 
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  # sentiment-guesser
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+ This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3734
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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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  ## Training procedure
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
 
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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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+ | 0.2921 | 1.0 | 3125 | 0.2793 |
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+ | 0.2303 | 2.0 | 6250 | 0.2741 |
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+ | 0.1488 | 3.0 | 9375 | 0.3239 |
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+ | 0.0802 | 4.0 | 12500 | 0.3506 |
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+ | 0.0494 | 5.0 | 15625 | 0.3734 |
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  ### Framework versions
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