update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,79 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
datasets:
|
| 6 |
+
- generator
|
| 7 |
+
model-index:
|
| 8 |
+
- name: bnc_spoken-cbt-notm-log-rarity-seed
|
| 9 |
+
results: []
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 13 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 14 |
+
|
| 15 |
+
# bnc_spoken-cbt-notm-log-rarity-seed
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the generator dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 4.1404
|
| 20 |
+
|
| 21 |
+
## Model description
|
| 22 |
+
|
| 23 |
+
More information needed
|
| 24 |
+
|
| 25 |
+
## Intended uses & limitations
|
| 26 |
+
|
| 27 |
+
More information needed
|
| 28 |
+
|
| 29 |
+
## Training and evaluation data
|
| 30 |
+
|
| 31 |
+
More information needed
|
| 32 |
+
|
| 33 |
+
## Training procedure
|
| 34 |
+
|
| 35 |
+
### Training hyperparameters
|
| 36 |
+
|
| 37 |
+
The following hyperparameters were used during training:
|
| 38 |
+
- learning_rate: 0.0005
|
| 39 |
+
- train_batch_size: 64
|
| 40 |
+
- eval_batch_size: 64
|
| 41 |
+
- seed: 42
|
| 42 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 43 |
+
- lr_scheduler_type: cosine
|
| 44 |
+
- lr_scheduler_warmup_steps: 1000
|
| 45 |
+
- num_epochs: 6
|
| 46 |
+
- mixed_precision_training: Native AMP
|
| 47 |
+
|
| 48 |
+
### Training results
|
| 49 |
+
|
| 50 |
+
| Training Loss | Epoch | Step | Validation Loss |
|
| 51 |
+
|:-------------:|:-----:|:-----:|:---------------:|
|
| 52 |
+
| 6.3631 | 0.29 | 500 | 5.3434 |
|
| 53 |
+
| 5.0481 | 0.59 | 1000 | 4.9361 |
|
| 54 |
+
| 4.7177 | 0.88 | 1500 | 4.7045 |
|
| 55 |
+
| 4.4593 | 1.17 | 2000 | 4.5683 |
|
| 56 |
+
| 4.3118 | 1.46 | 2500 | 4.4484 |
|
| 57 |
+
| 4.2082 | 1.76 | 3000 | 4.3453 |
|
| 58 |
+
| 4.0886 | 2.05 | 3500 | 4.2725 |
|
| 59 |
+
| 3.9027 | 2.34 | 4000 | 4.2271 |
|
| 60 |
+
| 3.8826 | 2.63 | 4500 | 4.1747 |
|
| 61 |
+
| 3.8396 | 2.93 | 5000 | 4.1241 |
|
| 62 |
+
| 3.645 | 3.22 | 5500 | 4.1184 |
|
| 63 |
+
| 3.5953 | 3.51 | 6000 | 4.0930 |
|
| 64 |
+
| 3.5812 | 3.81 | 6500 | 4.0604 |
|
| 65 |
+
| 3.4807 | 4.1 | 7000 | 4.0629 |
|
| 66 |
+
| 3.3286 | 4.39 | 7500 | 4.0557 |
|
| 67 |
+
| 3.325 | 4.68 | 8000 | 4.0463 |
|
| 68 |
+
| 3.3134 | 4.98 | 8500 | 4.0327 |
|
| 69 |
+
| 3.1583 | 5.27 | 9000 | 4.0488 |
|
| 70 |
+
| 3.1455 | 5.56 | 9500 | 4.0474 |
|
| 71 |
+
| 3.1459 | 5.85 | 10000 | 4.0466 |
|
| 72 |
+
|
| 73 |
+
|
| 74 |
+
### Framework versions
|
| 75 |
+
|
| 76 |
+
- Transformers 4.26.1
|
| 77 |
+
- Pytorch 1.11.0+cu113
|
| 78 |
+
- Datasets 2.13.0
|
| 79 |
+
- Tokenizers 0.13.3
|