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---
library_name: transformers
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: age_transcript_conv1
  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. -->

# age_transcript_conv1

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: 3.2240

## 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 4.7007        | 0.0254 | 1000  | 4.4922          |
| 4.2819        | 0.0508 | 2000  | 4.2123          |
| 4.1092        | 0.0762 | 3000  | 4.0324          |
| 3.9861        | 0.1016 | 4000  | 3.9267          |
| 3.9221        | 0.1270 | 5000  | 3.8582          |
| 3.8904        | 0.1524 | 6000  | 3.7809          |
| 3.7526        | 0.1778 | 7000  | 3.7252          |
| 3.7724        | 0.2032 | 8000  | 3.6846          |
| 3.6967        | 0.2285 | 9000  | 3.6293          |
| 3.5701        | 0.2539 | 10000 | 3.5902          |
| 3.676         | 0.2793 | 11000 | 3.5787          |
| 3.6092        | 0.3047 | 12000 | 3.5333          |
| 3.5105        | 0.3301 | 13000 | 3.5061          |
| 3.5298        | 0.3555 | 14000 | 3.4776          |
| 3.4857        | 0.3809 | 15000 | 3.4537          |
| 3.4688        | 0.4063 | 16000 | 3.4490          |
| 3.4914        | 0.4317 | 17000 | 3.4141          |
| 3.3866        | 0.4571 | 18000 | 3.3970          |
| 3.484         | 0.4825 | 19000 | 3.3963          |
| 3.4187        | 0.5079 | 20000 | 3.3733          |
| 3.2706        | 0.5333 | 21000 | 3.3546          |
| 3.4344        | 0.5587 | 22000 | 3.3640          |
| 3.3577        | 0.5841 | 23000 | 3.3337          |
| 3.3058        | 0.6095 | 24000 | 3.3364          |
| 3.3558        | 0.6349 | 25000 | 3.3195          |
| 3.2865        | 0.6603 | 26000 | 3.2988          |
| 3.3295        | 0.6856 | 27000 | 3.3054          |
| 3.3024        | 0.7110 | 28000 | 3.2867          |
| 3.1984        | 0.7364 | 29000 | 3.2751          |
| 3.3467        | 0.7618 | 30000 | 3.2792          |
| 3.3066        | 0.7872 | 31000 | 3.2647          |
| 3.1441        | 0.8126 | 32000 | 3.2606          |
| 3.3292        | 0.8380 | 33000 | 3.2656          |
| 3.2561        | 0.8634 | 34000 | 3.2444          |
| 3.2027        | 0.8888 | 35000 | 3.2549          |
| 3.264         | 0.9142 | 36000 | 3.2401          |
| 3.1928        | 0.9396 | 37000 | 3.2293          |
| 3.2385        | 0.9650 | 38000 | 3.2376          |
| 3.2274        | 0.9904 | 39000 | 3.2240          |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1