File size: 2,807 Bytes
8dc1ce6 |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased_fold_3_binary_v1
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. -->
# distilbert-base-uncased_fold_3_binary_v1
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9405
- F1: 0.7878
## 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 | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 289 | 0.4630 | 0.7897 |
| 0.3954 | 2.0 | 578 | 0.4549 | 0.7936 |
| 0.3954 | 3.0 | 867 | 0.6527 | 0.7868 |
| 0.1991 | 4.0 | 1156 | 0.7510 | 0.7951 |
| 0.1991 | 5.0 | 1445 | 0.9327 | 0.8000 |
| 0.095 | 6.0 | 1734 | 1.0974 | 0.7859 |
| 0.0347 | 7.0 | 2023 | 1.2692 | 0.7919 |
| 0.0347 | 8.0 | 2312 | 1.3718 | 0.7921 |
| 0.0105 | 9.0 | 2601 | 1.4679 | 0.7999 |
| 0.0105 | 10.0 | 2890 | 1.5033 | 0.8070 |
| 0.0079 | 11.0 | 3179 | 1.6074 | 0.8008 |
| 0.0079 | 12.0 | 3468 | 1.6921 | 0.7904 |
| 0.0053 | 13.0 | 3757 | 1.7079 | 0.7945 |
| 0.0054 | 14.0 | 4046 | 1.8361 | 0.7887 |
| 0.0054 | 15.0 | 4335 | 1.7695 | 0.7873 |
| 0.0046 | 16.0 | 4624 | 1.7934 | 0.7917 |
| 0.0046 | 17.0 | 4913 | 1.8036 | 0.8008 |
| 0.0064 | 18.0 | 5202 | 1.8780 | 0.7888 |
| 0.0064 | 19.0 | 5491 | 1.8943 | 0.7923 |
| 0.0032 | 20.0 | 5780 | 1.8694 | 0.7905 |
| 0.002 | 21.0 | 6069 | 1.9348 | 0.7869 |
| 0.002 | 22.0 | 6358 | 1.9578 | 0.7804 |
| 0.0036 | 23.0 | 6647 | 1.9438 | 0.7827 |
| 0.0036 | 24.0 | 6936 | 1.9386 | 0.7878 |
| 0.0011 | 25.0 | 7225 | 1.9405 | 0.7878 |
### Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
|