File size: 2,851 Bytes
dfa440d |
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 74 75 76 77 78 79 80 81 82 83 84 85 |
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cdp_hyl_fd
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. -->
# cdp_hyl_fd
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4997
- Accuracy: 0.8235
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7019 | 1.0 | 55 | 1.1939 | 0.5 |
| 0.1305 | 2.0 | 110 | 0.6574 | 0.7353 |
| 0.0242 | 3.0 | 165 | 0.5197 | 0.8235 |
| 0.0081 | 4.0 | 220 | 0.3666 | 0.8824 |
| 0.0051 | 5.0 | 275 | 0.4560 | 0.8529 |
| 0.0035 | 6.0 | 330 | 0.4470 | 0.8235 |
| 0.0026 | 7.0 | 385 | 0.4395 | 0.8529 |
| 0.0022 | 8.0 | 440 | 0.4486 | 0.8235 |
| 0.0018 | 9.0 | 495 | 0.4684 | 0.8235 |
| 0.0015 | 10.0 | 550 | 0.4644 | 0.8529 |
| 0.0013 | 11.0 | 605 | 0.4669 | 0.8235 |
| 0.0012 | 12.0 | 660 | 0.4657 | 0.8235 |
| 0.0011 | 13.0 | 715 | 0.4799 | 0.8235 |
| 0.001 | 14.0 | 770 | 0.4817 | 0.8235 |
| 0.0009 | 15.0 | 825 | 0.4998 | 0.8235 |
| 0.0008 | 16.0 | 880 | 0.4964 | 0.8235 |
| 0.0008 | 17.0 | 935 | 0.5025 | 0.8235 |
| 0.0007 | 18.0 | 990 | 0.4954 | 0.8235 |
| 0.0007 | 19.0 | 1045 | 0.4933 | 0.8235 |
| 0.0007 | 20.0 | 1100 | 0.5014 | 0.8235 |
| 0.0006 | 21.0 | 1155 | 0.4961 | 0.8235 |
| 0.0006 | 22.0 | 1210 | 0.4955 | 0.8235 |
| 0.0006 | 23.0 | 1265 | 0.4984 | 0.8235 |
| 0.0006 | 24.0 | 1320 | 0.4988 | 0.8235 |
| 0.0006 | 25.0 | 1375 | 0.4997 | 0.8235 |
### Framework versions
- Transformers 4.36.1
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|