Instructions to use anandNakat/my_awesome_opus_books_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anandNakat/my_awesome_opus_books_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("anandNakat/my_awesome_opus_books_model") model = AutoModelForSeq2SeqLM.from_pretrained("anandNakat/my_awesome_opus_books_model") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 0b13c1f
End of training
Browse files- README.md +10 -0
- generation_config.json +1 -0
README.md
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# my_awesome_opus_books_model
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This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
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## Model description
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- lr_scheduler_type: linear
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- num_epochs: 2
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### Framework versions
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- Transformers 4.33.3
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# my_awesome_opus_books_model
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This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2390
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## Model description
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- lr_scheduler_type: linear
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.0423 | 1.0 | 2000 | 0.3021 |
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| 0.0265 | 2.0 | 4000 | 0.2390 |
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### Framework versions
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- Transformers 4.33.3
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generation_config.json
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{
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"bos_token_id": 0,
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"decoder_start_token_id": 2,
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"early_stopping": true,
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{
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"_from_model_config": true,
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"bos_token_id": 0,
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"decoder_start_token_id": 2,
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"early_stopping": true,
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