File size: 3,810 Bytes
e4c89f9 b87a0e8 e4c89f9 7121d73 e4c89f9 7121d73 e4c89f9 adc7681 e4c89f9 adc7681 e4c89f9 5a33f19 e4c89f9 6f829ab e4c89f9 adc7681 e4c89f9 7121d73 e4c89f9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 |
---
license: apache-2.0
tags:
- generated_from_trainer
base_model: bert-large-uncased
model-index:
- name: pictalk
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. -->
# pictalk
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3395
## 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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.4213 | 1.0 | 25 | 3.2802 |
| 3.1204 | 2.0 | 50 | 2.8289 |
| 2.7337 | 3.0 | 75 | 2.5070 |
| 2.4701 | 4.0 | 100 | 2.1833 |
| 2.2536 | 5.0 | 125 | 2.0859 |
| 2.1284 | 6.0 | 150 | 2.0973 |
| 1.9703 | 7.0 | 175 | 1.8079 |
| 1.9372 | 8.0 | 200 | 1.8733 |
| 1.9115 | 9.0 | 225 | 1.7319 |
| 1.7705 | 10.0 | 250 | 1.8154 |
| 1.7454 | 11.0 | 275 | 1.6135 |
| 1.7338 | 12.0 | 300 | 1.6072 |
| 1.6741 | 13.0 | 325 | 1.4479 |
| 1.6552 | 14.0 | 350 | 1.6893 |
| 1.5546 | 15.0 | 375 | 1.5714 |
| 1.5905 | 16.0 | 400 | 1.6661 |
| 1.5136 | 17.0 | 425 | 1.6100 |
| 1.5403 | 18.0 | 450 | 1.5664 |
| 1.4947 | 19.0 | 475 | 1.4803 |
| 1.4654 | 20.0 | 500 | 1.6041 |
| 1.4449 | 21.0 | 525 | 1.4071 |
| 1.4817 | 22.0 | 550 | 1.5543 |
| 1.377 | 23.0 | 575 | 1.3897 |
| 1.4102 | 24.0 | 600 | 1.4572 |
| 1.3246 | 25.0 | 625 | 1.5699 |
| 1.3323 | 26.0 | 650 | 1.4316 |
| 1.2745 | 27.0 | 675 | 1.5004 |
| 1.2589 | 28.0 | 700 | 1.5209 |
| 1.3488 | 29.0 | 725 | 1.4734 |
| 1.301 | 30.0 | 750 | 1.5197 |
| 1.2824 | 31.0 | 775 | 1.5087 |
| 1.2771 | 32.0 | 800 | 1.4041 |
| 1.2794 | 33.0 | 825 | 1.5773 |
| 1.2343 | 34.0 | 850 | 1.3722 |
| 1.3235 | 35.0 | 875 | 1.5125 |
| 1.2567 | 36.0 | 900 | 1.3877 |
| 1.2682 | 37.0 | 925 | 1.5471 |
| 1.2028 | 38.0 | 950 | 1.3677 |
| 1.2059 | 39.0 | 975 | 1.4233 |
| 1.2103 | 40.0 | 1000 | 1.5361 |
| 1.1987 | 41.0 | 1025 | 1.5492 |
| 1.2853 | 42.0 | 1050 | 1.4274 |
| 1.2088 | 43.0 | 1075 | 1.5027 |
| 1.2573 | 44.0 | 1100 | 1.5138 |
| 1.2511 | 45.0 | 1125 | 1.4198 |
| 1.1932 | 46.0 | 1150 | 1.3065 |
| 1.1864 | 47.0 | 1175 | 1.4521 |
| 1.2362 | 48.0 | 1200 | 1.4576 |
| 1.215 | 49.0 | 1225 | 1.4246 |
| 1.2118 | 50.0 | 1250 | 1.3395 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
|