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all_abstracts_multi-qa-MiniLM-L6-cos-v1_final
howanching-clara/all_abstracts_multi-qa-MiniLM-L6-cos-v1_final
all_abstracts_multi-qa-MiniLM-L6-cos-v1_final is a text classification model from howanching-clara. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Apr 24, 2024
- Updated
- May 2, 2024
- SHA
- 3731ed4c
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
all_abstracts_multi-qa-MiniLM-L6-cos-v1
This model is a fine-tuned version of sentence-transformers/multi-qa-MiniLM-L6-cos-v1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.5678
- Accuracy: 0.4621
- Precision: 0.4621
- Recall: 0.4621
- F1: 0.4621
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 2.466 | 1.0 | 660 | 2.0039 | 0.3212 | 0.3212 | 0.3212 | 0.3212 |
| 2.0309 | 2.0 | 1320 | 1.8715 | 0.4061 | 0.4061 | 0.4061 | 0.4061 |
| 1.9092 | 3.0 | 1980 | 1.7737 | 0.4288 | 0.4288 | 0.4288 | 0.4288 |
| 1.6374 | 4.0 | 2640 | 1.7987 | 0.4606 | 0.4606 | 0.4606 | 0.4606 |
| 1.5152 | 5.0 | 3300 | 1.8548 | 0.4606 | 0.4606 | 0.4606 | 0.4606 |
| 1.4285 | 6.0 | 3960 | 1.8773 | 0.4712 | 0.4712 | 0.4712 | 0.4712 |
| 1.1618 | 7.0 | 4620 | 1.9726 | 0.4545 | 0.4545 | 0.4545 | 0.4545 |
| 1.104 | 8.0 | 5280 | 2.0739 | 0.4652 | 0.4652 | 0.4652 | 0.4652 |
| 1.025 | 9.0 | 5940 | 2.2104 | 0.4545 | 0.4545 | 0.4545 | 0.4545 |
| 0.9051 | 10.0 | 6600 | 2.2647 | 0.4545 | 0.4545 | 0.4545 | 0.4545 |
| 0.8191 | 11.0 | 7260 | 2.3455 | 0.4576 | 0.4576 | 0.4576 | 0.4576 |
| 0.8319 | 12.0 | 7920 | 2.4673 | 0.4652 | 0.4652 | 0.4652 | 0.4652 |
| 0.7634 | 13.0 | 8580 | 2.4986 | 0.4621 | 0.4621 | 0.4621 | 0.4621 |
| 0.7199 | 14.0 | 9240 | 2.5761 | 0.4636 | 0.4636 | 0.4636 | 0.4636 |
| 0.737 | 15.0 | 9900 | 2.5678 | 0.4621 | 0.4621 | 0.4621 | 0.4621 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu118
- Datasets 2.14.7
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Apr 24, 2024
- Updated
- May 2, 2024