|
--- |
|
license: apache-2.0 |
|
base_model: distilbert/distilbert-base-cased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
model-index: |
|
- name: distilbert-base-cased-airlines-news-multi-label-8-actions |
|
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-cased-airlines-news-multi-label-8-actions |
|
|
|
This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co./distilbert/distilbert-base-cased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2141 |
|
- F1: 0.9107 |
|
- Jaccard: 0.5749 |
|
|
|
## 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: 24 |
|
- eval_batch_size: 24 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 150 |
|
- num_epochs: 45 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 | Jaccard | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:| |
|
| No log | 1.0 | 76 | 0.4054 | 0.8583 | 0.4115 | |
|
| No log | 2.0 | 152 | 0.2956 | 0.8583 | 0.4115 | |
|
| No log | 3.0 | 228 | 0.2885 | 0.8583 | 0.4115 | |
|
| No log | 4.0 | 304 | 0.2807 | 0.8583 | 0.4115 | |
|
| No log | 5.0 | 380 | 0.2735 | 0.8583 | 0.4115 | |
|
| No log | 6.0 | 456 | 0.2668 | 0.8583 | 0.4115 | |
|
| 0.3504 | 7.0 | 532 | 0.2608 | 0.8709 | 0.4159 | |
|
| 0.3504 | 8.0 | 608 | 0.2550 | 0.8822 | 0.4226 | |
|
| 0.3504 | 9.0 | 684 | 0.2501 | 0.8930 | 0.4403 | |
|
| 0.3504 | 10.0 | 760 | 0.2462 | 0.8941 | 0.4779 | |
|
| 0.3504 | 11.0 | 836 | 0.2424 | 0.8907 | 0.4712 | |
|
| 0.3504 | 12.0 | 912 | 0.2385 | 0.8899 | 0.4757 | |
|
| 0.3504 | 13.0 | 988 | 0.2360 | 0.8930 | 0.5144 | |
|
| 0.2673 | 14.0 | 1064 | 0.2335 | 0.8931 | 0.5081 | |
|
| 0.2673 | 15.0 | 1140 | 0.2321 | 0.8921 | 0.5081 | |
|
| 0.2673 | 16.0 | 1216 | 0.2292 | 0.8964 | 0.5380 | |
|
| 0.2673 | 17.0 | 1292 | 0.2269 | 0.8975 | 0.5291 | |
|
| 0.2673 | 18.0 | 1368 | 0.2256 | 0.8962 | 0.5461 | |
|
| 0.2673 | 19.0 | 1444 | 0.2240 | 0.8968 | 0.5439 | |
|
| 0.2471 | 20.0 | 1520 | 0.2237 | 0.8973 | 0.5454 | |
|
| 0.2471 | 21.0 | 1596 | 0.2224 | 0.8971 | 0.5350 | |
|
| 0.2471 | 22.0 | 1672 | 0.2213 | 0.8985 | 0.5313 | |
|
| 0.2471 | 23.0 | 1748 | 0.2191 | 0.8982 | 0.5549 | |
|
| 0.2471 | 24.0 | 1824 | 0.2186 | 0.9072 | 0.5542 | |
|
| 0.2471 | 25.0 | 1900 | 0.2182 | 0.8993 | 0.5542 | |
|
| 0.2471 | 26.0 | 1976 | 0.2168 | 0.9071 | 0.5608 | |
|
| 0.2374 | 27.0 | 2052 | 0.2162 | 0.9091 | 0.5608 | |
|
| 0.2374 | 28.0 | 2128 | 0.2154 | 0.8998 | 0.5601 | |
|
| 0.2374 | 29.0 | 2204 | 0.2146 | 0.9095 | 0.5608 | |
|
| 0.2374 | 30.0 | 2280 | 0.2141 | 0.9083 | 0.5608 | |
|
| 0.2374 | 31.0 | 2356 | 0.2141 | 0.9107 | 0.5749 | |
|
| 0.2374 | 32.0 | 2432 | 0.2136 | 0.9103 | 0.5704 | |
|
| 0.2325 | 33.0 | 2508 | 0.2140 | 0.9052 | 0.5542 | |
|
| 0.2325 | 34.0 | 2584 | 0.2125 | 0.9084 | 0.5608 | |
|
| 0.2325 | 35.0 | 2660 | 0.2118 | 0.9091 | 0.5623 | |
|
| 0.2325 | 36.0 | 2736 | 0.2118 | 0.9092 | 0.5667 | |
|
| 0.2325 | 37.0 | 2812 | 0.2115 | 0.9072 | 0.5608 | |
|
| 0.2325 | 38.0 | 2888 | 0.2118 | 0.9081 | 0.5667 | |
|
| 0.2325 | 39.0 | 2964 | 0.2110 | 0.9080 | 0.5623 | |
|
| 0.2293 | 40.0 | 3040 | 0.2111 | 0.9092 | 0.5667 | |
|
| 0.2293 | 41.0 | 3116 | 0.2110 | 0.9087 | 0.5667 | |
|
| 0.2293 | 42.0 | 3192 | 0.2109 | 0.9085 | 0.5623 | |
|
| 0.2293 | 43.0 | 3268 | 0.2108 | 0.9092 | 0.5667 | |
|
| 0.2293 | 44.0 | 3344 | 0.2107 | 0.9085 | 0.5623 | |
|
| 0.2293 | 45.0 | 3420 | 0.2107 | 0.9085 | 0.5623 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.1 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
