Instructions to use badokorach/xlm-roberta-base-finetuned-mlqa-Mixed-AGRIC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use badokorach/xlm-roberta-base-finetuned-mlqa-Mixed-AGRIC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="badokorach/xlm-roberta-base-finetuned-mlqa-Mixed-AGRIC")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("badokorach/xlm-roberta-base-finetuned-mlqa-Mixed-AGRIC") model = AutoModelForQuestionAnswering.from_pretrained("badokorach/xlm-roberta-base-finetuned-mlqa-Mixed-AGRIC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit 路
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Parent(s): ff4157b
Training in progress epoch 9
Browse files- README.md +3 -2
- tf_model.h5 +1 -1
README.md
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This model is a fine-tuned version of [badokorach/roberta-base-squad2-agric-181223](https://huggingface.co/badokorach/roberta-base-squad2-agric-181223) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 1.
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- Validation Loss: 0.0
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- Epoch:
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## Model description
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### Framework versions
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This model is a fine-tuned version of [badokorach/roberta-base-squad2-agric-181223](https://huggingface.co/badokorach/roberta-base-squad2-agric-181223) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 1.7330
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- Validation Loss: 0.0
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- Epoch: 9
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## Model description
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| 2.1666 | 0.0 | 6 |
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| 2.0118 | 0.0 | 7 |
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| 1.8718 | 0.0 | 8 |
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| 1.7330 | 0.0 | 9 |
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### Framework versions
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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size 1110105320
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