deberta-v3-large-survey-new_fact_related_passage-rater
This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2316
- Krippendorff: 0.9171
- Spearman: 0.9146
- Absolute Agreement: 0.9372
- Agreement Within One: 0.9874
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: 6e-06
- 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
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Krippendorff | Spearman | Absolute Agreement | Agreement Within One |
---|---|---|---|---|---|---|---|
No log | 1.0 | 50 | 1.9025 | -0.0055 | nan | 0.0833 | 0.6389 |
No log | 2.0 | 100 | 1.9012 | 0.1665 | 0.2932 | 0.1528 | 0.8611 |
No log | 3.0 | 150 | 1.9013 | -0.5318 | nan | 0.1806 | 1.0 |
No log | 4.0 | 200 | 1.9030 | -0.5318 | nan | 0.1806 | 1.0 |
No log | 5.0 | 250 | 1.9633 | -0.3932 | -0.1362 | 0.1528 | 0.8889 |
No log | 6.0 | 300 | 2.1312 | -0.3716 | -0.3587 | 0.0556 | 0.7361 |
No log | 7.0 | 350 | 2.1081 | -0.2882 | -0.1942 | 0.1111 | 0.8056 |
No log | 8.0 | 400 | 2.0798 | -0.2532 | -0.1339 | 0.1806 | 0.875 |
No log | 9.0 | 450 | 2.0693 | -0.2269 | -0.1385 | 0.25 | 0.5694 |
1.6529 | 10.0 | 500 | 2.0939 | -0.2456 | -0.2515 | 0.1667 | 0.6667 |
1.6529 | 11.0 | 550 | 2.1227 | -0.0758 | 0.0820 | 0.2639 | 0.6111 |
1.6529 | 12.0 | 600 | 2.0465 | -0.1802 | 0.0413 | 0.3056 | 0.5694 |
1.6529 | 13.0 | 650 | 2.0901 | -0.1164 | -0.0485 | 0.2639 | 0.625 |
1.6529 | 14.0 | 700 | 2.1685 | 0.2526 | 0.3009 | 0.2778 | 0.9028 |
1.6529 | 15.0 | 750 | 2.1592 | 0.2603 | 0.2661 | 0.3194 | 0.7083 |
1.6529 | 16.0 | 800 | 2.3096 | 0.2225 | 0.2235 | 0.2917 | 0.7778 |
1.6529 | 17.0 | 850 | 2.2947 | 0.2268 | 0.2128 | 0.3056 | 0.7222 |
1.6529 | 18.0 | 900 | 2.3396 | 0.0808 | 0.1413 | 0.3056 | 0.6528 |
1.6529 | 19.0 | 950 | 2.6040 | -0.0037 | 0.1140 | 0.3056 | 0.6389 |
0.7915 | 20.0 | 1000 | 2.5205 | 0.2986 | 0.2466 | 0.1944 | 0.8194 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1
- Downloads last month
- 13