End of training
Browse files
README.md
ADDED
|
@@ -0,0 +1,89 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: gokuls/HBERTv1_48_L12_H256_A4
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
datasets:
|
| 6 |
+
- massive
|
| 7 |
+
metrics:
|
| 8 |
+
- accuracy
|
| 9 |
+
model-index:
|
| 10 |
+
- name: HBERTv1_48_L12_H256_A4_massive
|
| 11 |
+
results:
|
| 12 |
+
- task:
|
| 13 |
+
name: Text Classification
|
| 14 |
+
type: text-classification
|
| 15 |
+
dataset:
|
| 16 |
+
name: massive
|
| 17 |
+
type: massive
|
| 18 |
+
config: en-US
|
| 19 |
+
split: validation
|
| 20 |
+
args: en-US
|
| 21 |
+
metrics:
|
| 22 |
+
- name: Accuracy
|
| 23 |
+
type: accuracy
|
| 24 |
+
value: 0.7338908017707821
|
| 25 |
+
---
|
| 26 |
+
|
| 27 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 28 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 29 |
+
|
| 30 |
+
# HBERTv1_48_L12_H256_A4_massive
|
| 31 |
+
|
| 32 |
+
This model is a fine-tuned version of [gokuls/HBERTv1_48_L12_H256_A4](https://huggingface.co/gokuls/HBERTv1_48_L12_H256_A4) on the massive dataset.
|
| 33 |
+
It achieves the following results on the evaluation set:
|
| 34 |
+
- Loss: 1.1699
|
| 35 |
+
- Accuracy: 0.7339
|
| 36 |
+
|
| 37 |
+
## Model description
|
| 38 |
+
|
| 39 |
+
More information needed
|
| 40 |
+
|
| 41 |
+
## Intended uses & limitations
|
| 42 |
+
|
| 43 |
+
More information needed
|
| 44 |
+
|
| 45 |
+
## Training and evaluation data
|
| 46 |
+
|
| 47 |
+
More information needed
|
| 48 |
+
|
| 49 |
+
## Training procedure
|
| 50 |
+
|
| 51 |
+
### Training hyperparameters
|
| 52 |
+
|
| 53 |
+
The following hyperparameters were used during training:
|
| 54 |
+
- learning_rate: 5e-05
|
| 55 |
+
- train_batch_size: 64
|
| 56 |
+
- eval_batch_size: 64
|
| 57 |
+
- seed: 33
|
| 58 |
+
- distributed_type: multi-GPU
|
| 59 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 60 |
+
- lr_scheduler_type: linear
|
| 61 |
+
- num_epochs: 15
|
| 62 |
+
|
| 63 |
+
### Training results
|
| 64 |
+
|
| 65 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 66 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| 67 |
+
| 3.7238 | 1.0 | 180 | 3.4052 | 0.1382 |
|
| 68 |
+
| 3.1325 | 2.0 | 360 | 2.8875 | 0.2022 |
|
| 69 |
+
| 2.7162 | 3.0 | 540 | 2.5311 | 0.3030 |
|
| 70 |
+
| 2.4123 | 4.0 | 720 | 2.3315 | 0.3576 |
|
| 71 |
+
| 2.1258 | 5.0 | 900 | 2.0547 | 0.4186 |
|
| 72 |
+
| 1.8697 | 6.0 | 1080 | 1.8215 | 0.4889 |
|
| 73 |
+
| 1.6446 | 7.0 | 1260 | 1.6681 | 0.5421 |
|
| 74 |
+
| 1.4509 | 8.0 | 1440 | 1.5200 | 0.5853 |
|
| 75 |
+
| 1.2995 | 9.0 | 1620 | 1.4177 | 0.6188 |
|
| 76 |
+
| 1.1585 | 10.0 | 1800 | 1.3337 | 0.6557 |
|
| 77 |
+
| 1.0714 | 11.0 | 1980 | 1.2620 | 0.7059 |
|
| 78 |
+
| 0.9816 | 12.0 | 2160 | 1.2374 | 0.7147 |
|
| 79 |
+
| 0.9053 | 13.0 | 2340 | 1.1849 | 0.7290 |
|
| 80 |
+
| 0.8582 | 14.0 | 2520 | 1.1721 | 0.7324 |
|
| 81 |
+
| 0.8253 | 15.0 | 2700 | 1.1699 | 0.7339 |
|
| 82 |
+
|
| 83 |
+
|
| 84 |
+
### Framework versions
|
| 85 |
+
|
| 86 |
+
- Transformers 4.34.0
|
| 87 |
+
- Pytorch 1.14.0a0+410ce96
|
| 88 |
+
- Datasets 2.14.5
|
| 89 |
+
- Tokenizers 0.14.0
|