| | --- |
| | license: apache-2.0 |
| | base_model: distilbert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: message-genre |
| | 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. --> |
| |
|
| | # message-genre |
| |
|
| | 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: 1.5875 |
| | - Accuracy: 0.4339 |
| |
|
| | ## 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: 5e-05 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 1.0 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | No log | 0.06 | 100 | 1.8239 | 0.3638 | |
| | | No log | 0.13 | 200 | 1.7266 | 0.3971 | |
| | | No log | 0.19 | 300 | 1.6873 | 0.4040 | |
| | | No log | 0.25 | 400 | 1.6609 | 0.4188 | |
| | | 1.8118 | 0.32 | 500 | 1.6674 | 0.4048 | |
| | | 1.8118 | 0.38 | 600 | 1.6381 | 0.4172 | |
| | | 1.8118 | 0.45 | 700 | 1.6437 | 0.4156 | |
| | | 1.8118 | 0.51 | 800 | 1.6378 | 0.4143 | |
| | | 1.8118 | 0.57 | 900 | 1.6301 | 0.4214 | |
| | | 1.6738 | 0.64 | 1000 | 1.6106 | 0.4320 | |
| | | 1.6738 | 0.7 | 1100 | 1.6089 | 0.4259 | |
| | | 1.6738 | 0.76 | 1200 | 1.5988 | 0.4299 | |
| | | 1.6738 | 0.83 | 1300 | 1.5951 | 0.4347 | |
| | | 1.6738 | 0.89 | 1400 | 1.5896 | 0.4320 | |
| | | 1.6488 | 0.96 | 1500 | 1.5875 | 0.4339 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.32.1 |
| | - Pytorch 2.0.1 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.13.3 |
| |
|
