Hugging Face's logo

dahe827
/
distilbert-base-cased-airlines-news-multi-label-8-actions

Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
distilbert-base-cased-airlines-news-multi-label-8-actions / README.md
dahe827's picture
dahe827
End of training
cd7bbdb verified
preview code
|
raw
history blame contribute delete
4.63 kB
metadata
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: []

distilbert-base-cased-airlines-news-multi-label-8-actions

This model is a fine-tuned version of 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