depression_suggestion
This model is a fine-tuned version of distilgpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3740
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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 70
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 1.0 | 3 | 60.7965 |
No log | 2.0 | 6 | 60.5778 |
No log | 3.0 | 9 | 60.1954 |
No log | 4.0 | 12 | 59.6487 |
No log | 5.0 | 15 | 58.9372 |
No log | 6.0 | 18 | 58.0582 |
No log | 7.0 | 21 | 57.0106 |
No log | 8.0 | 24 | 55.7910 |
No log | 9.0 | 27 | 54.3934 |
No log | 10.0 | 30 | 52.8099 |
No log | 11.0 | 33 | 51.0219 |
No log | 12.0 | 36 | 49.0127 |
No log | 13.0 | 39 | 46.7522 |
No log | 14.0 | 42 | 44.2033 |
No log | 15.0 | 45 | 41.3146 |
No log | 16.0 | 48 | 37.9982 |
No log | 17.0 | 51 | 34.2236 |
No log | 18.0 | 54 | 29.8068 |
No log | 19.0 | 57 | 24.9750 |
No log | 20.0 | 60 | 20.0707 |
No log | 21.0 | 63 | 15.5166 |
No log | 22.0 | 66 | 12.0328 |
No log | 23.0 | 69 | 9.1012 |
No log | 24.0 | 72 | 7.2116 |
No log | 25.0 | 75 | 6.3149 |
No log | 26.0 | 78 | 5.8127 |
No log | 27.0 | 81 | 5.4548 |
No log | 28.0 | 84 | 5.1684 |
No log | 29.0 | 87 | 4.8927 |
No log | 30.0 | 90 | 4.6128 |
No log | 31.0 | 93 | 4.3782 |
No log | 32.0 | 96 | 4.1996 |
No log | 33.0 | 99 | 4.0981 |
No log | 34.0 | 102 | 4.0022 |
No log | 35.0 | 105 | 3.9224 |
No log | 36.0 | 108 | 3.8381 |
No log | 37.0 | 111 | 3.7660 |
No log | 38.0 | 114 | 3.6887 |
No log | 39.0 | 117 | 3.6483 |
No log | 40.0 | 120 | 3.6020 |
No log | 41.0 | 123 | 3.5590 |
No log | 42.0 | 126 | 3.5199 |
No log | 43.0 | 129 | 3.4646 |
No log | 44.0 | 132 | 3.4098 |
No log | 45.0 | 135 | 3.3684 |
No log | 46.0 | 138 | 3.3290 |
No log | 47.0 | 141 | 3.3113 |
No log | 48.0 | 144 | 3.3033 |
No log | 49.0 | 147 | 3.2928 |
No log | 50.0 | 150 | 3.2776 |
No log | 51.0 | 153 | 3.2587 |
No log | 52.0 | 156 | 3.2487 |
No log | 53.0 | 159 | 3.2390 |
No log | 54.0 | 162 | 3.2318 |
No log | 55.0 | 165 | 3.2311 |
No log | 56.0 | 168 | 3.2377 |
No log | 57.0 | 171 | 3.2554 |
No log | 58.0 | 174 | 3.2720 |
No log | 59.0 | 177 | 3.2781 |
No log | 60.0 | 180 | 3.2882 |
No log | 61.0 | 183 | 3.3089 |
No log | 62.0 | 186 | 3.3352 |
No log | 63.0 | 189 | 3.3519 |
No log | 64.0 | 192 | 3.3233 |
No log | 65.0 | 195 | 3.3028 |
No log | 66.0 | 198 | 3.3153 |
No log | 67.0 | 201 | 3.3422 |
No log | 68.0 | 204 | 3.3753 |
No log | 69.0 | 207 | 3.4003 |
No log | 70.0 | 210 | 3.3740 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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