File size: 2,387 Bytes
506dd49 |
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 |
---
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: electra-base-discriminator_Synonym-wordnet
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. -->
# electra-base-discriminator_Synonym-wordnet
This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2211
- Accuracy: 0.9267
- F1: 0.9267
- Precision: 0.9267
- Recall: 0.9267
## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.932 | 1.0 | 91 | 0.8735 | 0.6412 | 0.5915 | 0.6417 | 0.6412 |
| 0.426 | 2.0 | 182 | 0.3389 | 0.9002 | 0.9004 | 0.9008 | 0.9002 |
| 0.259 | 3.0 | 273 | 0.2577 | 0.9048 | 0.9039 | 0.9070 | 0.9048 |
| 0.1619 | 4.0 | 364 | 0.2211 | 0.9267 | 0.9267 | 0.9267 | 0.9267 |
| 0.1574 | 5.0 | 455 | 0.3301 | 0.8955 | 0.8959 | 0.9045 | 0.8955 |
| 0.0929 | 6.0 | 546 | 0.3284 | 0.9064 | 0.9054 | 0.9066 | 0.9064 |
| 0.1079 | 7.0 | 637 | 0.3467 | 0.9002 | 0.9003 | 0.9040 | 0.9002 |
| 0.0927 | 8.0 | 728 | 0.3817 | 0.9002 | 0.8993 | 0.9056 | 0.9002 |
| 0.0876 | 9.0 | 819 | 0.3524 | 0.9048 | 0.9044 | 0.9047 | 0.9048 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
|