metadata
library_name: transformers
license: apache-2.0
base_model: albert/albert-xlarge-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 88baaa0fc0d014bbfbf8077c9420beea
results: []
88baaa0fc0d014bbfbf8077c9420beea
This model is a fine-tuned version of albert/albert-xlarge-v2 on the ccdv/patent-classification [abstract] dataset. It achieves the following results on the evaluation set:
- Loss: 1.9926
- Data Size: 1.0
- Epoch Runtime: 145.0872
- Accuracy: 0.2218
- F1 Macro: 0.0403
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro |
|---|---|---|---|---|---|---|---|
| No log | 0 | 0 | 2.4026 | 0 | 9.6523 | 0.1004 | 0.0203 |
| No log | 1 | 781 | 2.0320 | 0.0078 | 11.3637 | 0.1538 | 0.0372 |
| No log | 2 | 1562 | 2.0092 | 0.0156 | 11.9116 | 0.1510 | 0.0292 |
| No log | 3 | 2343 | 2.0049 | 0.0312 | 14.1118 | 0.2071 | 0.0381 |
| 0.0454 | 4 | 3124 | 2.0001 | 0.0625 | 18.2314 | 0.2218 | 0.0403 |
| 2.0154 | 5 | 3905 | 1.9943 | 0.125 | 26.8018 | 0.2218 | 0.0403 |
| 2.0269 | 6 | 4686 | 1.9923 | 0.25 | 43.9274 | 0.2071 | 0.0381 |
| 1.9998 | 7 | 5467 | 1.9855 | 0.5 | 77.6442 | 0.2071 | 0.0381 |
| 1.9763 | 8.0 | 6248 | 1.9884 | 1.0 | 145.9947 | 0.2161 | 0.0648 |
| 1.972 | 9.0 | 7029 | 1.9885 | 1.0 | 145.3029 | 0.2071 | 0.0381 |
| 1.985 | 10.0 | 7810 | 1.9864 | 1.0 | 145.0537 | 0.2218 | 0.0403 |
| 1.9704 | 11.0 | 8591 | 1.9926 | 1.0 | 145.0872 | 0.2218 | 0.0403 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1