File size: 1,687 Bytes
03a494a e6ab41e 03a494a e6ab41e 03a494a e6ab41e 03a494a e6ab41e 03ac1d8 03a494a e6ab41e 03a494a e6ab41e 03a494a e6ab41e 03a494a e6ab41e 03a494a e6ab41e 03a494a e6ab41e 03a494a e6ab41e 03a494a e6ab41e 03a494a e6ab41e 03a494a e6ab41e 03a494a e6ab41e 03ac1d8 03a494a e6ab41e 03a494a e6ab41e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 |
---
library_name: transformers
license: apache-2.0
base_model: amberoad/bert-multilingual-passage-reranking-msmarco
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: category_predictor
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. -->
# category_predictor
This model is a fine-tuned version of [amberoad/bert-multilingual-passage-reranking-msmarco](https://huggingface.co/amberoad/bert-multilingual-passage-reranking-msmarco) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9181
- Accuracy: 0.8626
## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.9646 | 1.0 | 152248 | 1.3476 | 0.7807 |
| 0.611 | 2.0 | 304496 | 1.0336 | 0.8401 |
| 0.4423 | 3.0 | 456744 | 0.9181 | 0.8626 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
|