File size: 3,344 Bytes
9a2dd98 |
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 |
---
library_name: transformers
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: random_transcript_conv
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. -->
# random_transcript_conv
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2220
## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: reduce_lr_on_plateau
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 4.7264 | 0.0254 | 1000 | 4.4961 |
| 4.2766 | 0.0508 | 2000 | 4.2143 |
| 4.1231 | 0.0762 | 3000 | 4.0323 |
| 4.0307 | 0.1016 | 4000 | 3.9221 |
| 3.8887 | 0.1270 | 5000 | 3.8578 |
| 3.8689 | 0.1524 | 6000 | 3.7800 |
| 3.7808 | 0.1778 | 7000 | 3.7245 |
| 3.742 | 0.2032 | 8000 | 3.6854 |
| 3.7303 | 0.2285 | 9000 | 3.6259 |
| 3.5985 | 0.2539 | 10000 | 3.6000 |
| 3.6448 | 0.2793 | 11000 | 3.5646 |
| 3.6531 | 0.3047 | 12000 | 3.5310 |
| 3.463 | 0.3301 | 13000 | 3.5120 |
| 3.5609 | 0.3555 | 14000 | 3.4827 |
| 3.5348 | 0.3809 | 15000 | 3.4513 |
| 3.4552 | 0.4063 | 16000 | 3.4491 |
| 3.4829 | 0.4317 | 17000 | 3.4177 |
| 3.4333 | 0.4571 | 18000 | 3.3998 |
| 3.4369 | 0.4825 | 19000 | 3.3927 |
| 3.4465 | 0.5079 | 20000 | 3.3694 |
| 3.2959 | 0.5333 | 21000 | 3.3755 |
| 3.3914 | 0.5587 | 22000 | 3.3508 |
| 3.419 | 0.5841 | 23000 | 3.3296 |
| 3.2619 | 0.6095 | 24000 | 3.3346 |
| 3.3485 | 0.6349 | 25000 | 3.3173 |
| 3.3355 | 0.6603 | 26000 | 3.3090 |
| 3.3004 | 0.6856 | 27000 | 3.3027 |
| 3.3105 | 0.7110 | 28000 | 3.2894 |
| 3.2625 | 0.7364 | 29000 | 3.2808 |
| 3.3031 | 0.7618 | 30000 | 3.2878 |
| 3.3047 | 0.7872 | 31000 | 3.2691 |
| 3.1521 | 0.8126 | 32000 | 3.2749 |
| 3.2836 | 0.8380 | 33000 | 3.2561 |
| 3.2872 | 0.8634 | 34000 | 3.2511 |
| 3.1762 | 0.8888 | 35000 | 3.2519 |
| 3.2412 | 0.9142 | 36000 | 3.2455 |
| 3.2428 | 0.9396 | 37000 | 3.2323 |
| 3.2216 | 0.9650 | 38000 | 3.2419 |
| 3.2271 | 0.9904 | 39000 | 3.2220 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
|