File size: 2,421 Bytes
261c35f 1d58f43 261c35f 1d58f43 261c35f 1d58f43 7462d9e 1d58f43 261c35f a61bda3 261c35f |
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 |
---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: DLL888/deberta-v3-base-squad
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# DLL888/deberta-v3-base-squad
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the [SQuAD](https://huggingface.co/datasets/squad) dataset.
It achieves the following results on the evaluation set:
- Exact Match: 88.08893093661305
- F1: 93.75543944888847
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training Machine
Trained in Google Colab Pro with the following specs:
- A100-SXM4-40GB
- NVIDIA-SMI 460.32.03
- Driver Version: 460.32.03
- CUDA Version: 11.2
Training took about 26 minutes for two epochs.
### Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 10538, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 500, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 1.0540 | 0.7261 | 0.6885 | 0.7617 | 0.7841 | 0.7530 | 0 |
| 0.6248 | 0.8212 | 0.7777 | 0.7594 | 0.7873 | 0.7569 | 1 |
### Framework versions
- Transformers 4.24.0
- TensorFlow 2.9.2
- Datasets 2.7.1
- Tokenizers 0.13.2
|