Instructions to use LongRiver/transformer_QAVi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LongRiver/transformer_QAVi with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="LongRiver/transformer_QAVi")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("LongRiver/transformer_QAVi") model = AutoModelForQuestionAnswering.from_pretrained("LongRiver/transformer_QAVi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress epoch 1
Browse files
README.md
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This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss:
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- Train End Logits Accuracy: 0.
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- Train Start Logits Accuracy: 0.
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- Validation Loss: 2.
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- Validation End Logits Accuracy: 0.
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- Validation Start Logits Accuracy: 0.
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- Epoch:
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## Model description
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| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
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|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
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| 2.3715 | 0.5054 | 0.4994 | 2.0790 | 0.5204 | 0.4818 | 0 |
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### Framework versions
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This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 1.6965
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- Train End Logits Accuracy: 0.5926
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- Train Start Logits Accuracy: 0.5670
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- Validation Loss: 2.0530
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- Validation End Logits Accuracy: 0.5323
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- Validation Start Logits Accuracy: 0.5011
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- Epoch: 1
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## Model description
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| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
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|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
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| 2.3715 | 0.5054 | 0.4994 | 2.0790 | 0.5204 | 0.4818 | 0 |
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| 1.6965 | 0.5926 | 0.5670 | 2.0530 | 0.5323 | 0.5011 | 1 |
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### Framework versions
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logs/train/events.out.tfevents.1714957848.f7da57357404.85.0.v2
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logs/validation/events.out.tfevents.1714958638.f7da57357404.85.1.v2
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tf_model.h5
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