File size: 2,208 Bytes
d8cf373 |
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 65 66 67 68 69 70 71 72 73 |
---
library_name: transformers
license: apache-2.0
base_model: cross-encoder/nli-deberta-v3-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: enli-deberta-v3-large_10
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. -->
# enli-deberta-v3-large_10
This model is a fine-tuned version of [cross-encoder/nli-deberta-v3-large](https://huggingface.co/cross-encoder/nli-deberta-v3-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8908
- Accuracy: 0.9083
- F1: 0.9088
## 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: 16
- eval_batch_size: 16
- 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: cosine
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.2817 | 1.0 | 3516 | 0.2948 | 0.9042 | 0.9045 |
| 0.1676 | 2.0 | 7032 | 0.3862 | 0.9029 | 0.9033 |
| 0.1199 | 3.0 | 10548 | 0.5174 | 0.9017 | 0.9021 |
| 0.0501 | 4.0 | 14064 | 0.6014 | 0.9039 | 0.9043 |
| 0.0489 | 5.0 | 17580 | 0.7007 | 0.9034 | 0.9039 |
| 0.0173 | 6.0 | 21096 | 0.7448 | 0.9049 | 0.9056 |
| 0.0142 | 7.0 | 24612 | 0.7086 | 0.9062 | 0.9068 |
| 0.0003 | 8.0 | 28128 | 0.8314 | 0.9074 | 0.9079 |
| 0.0059 | 9.0 | 31644 | 0.8942 | 0.9078 | 0.9083 |
| 0.0 | 10.0 | 35160 | 0.8908 | 0.9083 | 0.9088 |
### Framework versions
- Transformers 4.52.4
- Pytorch 2.7.1+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1
|