Instructions to use eunyounglee/mBART_translator_json_hyperparameter_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eunyounglee/mBART_translator_json_hyperparameter_1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("eunyounglee/mBART_translator_json_hyperparameter_1") model = AutoModelForSeq2SeqLM.from_pretrained("eunyounglee/mBART_translator_json_hyperparameter_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from eunyounglee/mBART_translator_json_hyperparameter_1: direct link, hf CLI and curl.
- Browser
- Download file 1.72 kB
-
https://huggingface.co/eunyounglee/mBART_translator_json_hyperparameter_1/resolve/main/README.md
- Command line
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hf download hf://eunyounglee/mBART_translator_json_hyperparameter_1/README.md
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curl -L -o README.md https://huggingface.co/eunyounglee/mBART_translator_json_hyperparameter_1/resolve/main/README.md
1.72 kB
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - bleu | |
| model-index: | |
| - name: mBART_translator_json_hyperparameter_1 | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # mBART_translator_json_hyperparameter_1 | |
| This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0871 | |
| - Bleu: 86.6567 | |
| - Gen Len: 43.0648 | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 1e-05 | |
| - train_batch_size: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 5 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| | |
| | 2.4912 | 1.0 | 1998 | 0.6319 | 66.5947 | 80.0315 | | |
| | 1.4069 | 2.0 | 3996 | 0.2170 | 72.413 | 64.2111 | | |
| | 1.0829 | 3.0 | 5994 | 0.1315 | 78.7786 | 40.3136 | | |
| | 0.8977 | 4.0 | 7992 | 0.0979 | 84.3878 | 42.5152 | | |
| | 0.8452 | 5.0 | 9990 | 0.0871 | 86.6567 | 43.0648 | | |
| ### Framework versions | |
| - Transformers 4.23.1 | |
| - Pytorch 1.12.1+cu113 | |
| - Datasets 2.6.0 | |
| - Tokenizers 0.13.1 | |