transformers tf gpt2 text-generation generated_from_keras_callback base_model:gpt2 license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: mit
base_model: gpt2
tags:
- generated_from_keras_callback
model-index:
- name: ashishbaraiya/my-tweets-finetuned
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# ashishbaraiya/my-tweets-finetuned

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:
- Train Loss: 0.0656
- Validation Loss: 3.2945
- Epoch: 98

## 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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 4500, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 9.3483     | 8.3624          | 0     |
| 7.2778     | 6.9685          | 1     |
| 5.9195     | 6.2234          | 2     |
| 5.0730     | 5.6830          | 3     |
| 4.4703     | 5.3916          | 4     |
| 3.8427     | 4.8847          | 5     |
| 3.3641     | 4.5318          | 6     |
| 2.8373     | 4.3084          | 7     |
| 2.4261     | 4.0802          | 8     |
| 2.0691     | 3.8920          | 9     |
| 1.8213     | 3.8208          | 10    |
| 1.5922     | 3.6103          | 11    |
| 1.3694     | 3.5038          | 12    |
| 1.1764     | 3.3149          | 13    |
| 1.0135     | 3.2981          | 14    |
| 0.8874     | 3.2975          | 15    |
| 0.7716     | 3.2103          | 16    |
| 0.6679     | 3.3297          | 17    |
| 0.5770     | 3.2517          | 18    |
| 0.5098     | 3.0959          | 19    |
| 0.4403     | 3.1526          | 20    |
| 0.3791     | 2.9750          | 21    |
| 0.3367     | 3.0588          | 22    |
| 0.3027     | 3.0408          | 23    |
| 0.2617     | 3.1930          | 24    |
| 0.2387     | 3.1227          | 25    |
| 0.2175     | 3.0582          | 26    |
| 0.2062     | 3.1239          | 27    |
| 0.1868     | 3.0407          | 28    |
| 0.1746     | 3.2357          | 29    |
| 0.1657     | 3.1285          | 30    |
| 0.1536     | 3.2110          | 31    |
| 0.1512     | 3.1890          | 32    |
| 0.1447     | 3.1713          | 33    |
| 0.1426     | 3.1498          | 34    |
| 0.1369     | 3.1877          | 35    |
| 0.1327     | 3.2019          | 36    |
| 0.1303     | 3.0486          | 37    |
| 0.1213     | 3.1264          | 38    |
| 0.1204     | 3.1468          | 39    |
| 0.1206     | 3.1846          | 40    |
| 0.1125     | 3.1880          | 41    |
| 0.1113     | 3.1980          | 42    |
| 0.1098     | 3.1759          | 43    |
| 0.1071     | 3.1385          | 44    |
| 0.1055     | 3.1730          | 45    |
| 0.1024     | 3.1820          | 46    |
| 0.0995     | 3.1252          | 47    |
| 0.0995     | 3.1279          | 48    |
| 0.1004     | 3.2428          | 49    |
| 0.0982     | 3.1116          | 50    |
| 0.0957     | 3.2210          | 51    |
| 0.0936     | 3.1351          | 52    |
| 0.0917     | 3.1618          | 53    |
| 0.0930     | 3.1924          | 54    |
| 0.0929     | 3.2831          | 55    |
| 0.0889     | 3.2458          | 56    |
| 0.0913     | 3.2061          | 57    |
| 0.0899     | 3.4128          | 58    |
| 0.0880     | 3.2114          | 59    |
| 0.0869     | 3.2738          | 60    |
| 0.0878     | 3.1723          | 61    |
| 0.0844     | 3.1465          | 62    |
| 0.0846     | 3.1106          | 63    |
| 0.0841     | 3.2216          | 64    |
| 0.0824     | 3.2971          | 65    |
| 0.0823     | 3.2267          | 66    |
| 0.0811     | 3.2503          | 67    |
| 0.0823     | 3.1981          | 68    |
| 0.0808     | 3.2618          | 69    |
| 0.0803     | 3.1607          | 70    |
| 0.0786     | 3.3295          | 71    |
| 0.0801     | 3.2952          | 72    |
| 0.0777     | 3.2545          | 73    |
| 0.0764     | 3.1248          | 74    |
| 0.0772     | 3.2185          | 75    |
| 0.0758     | 3.3147          | 76    |
| 0.0764     | 3.1842          | 77    |
| 0.0758     | 3.2346          | 78    |
| 0.0739     | 3.2914          | 79    |
| 0.0738     | 3.2163          | 80    |
| 0.0738     | 3.3555          | 81    |
| 0.0731     | 3.0948          | 82    |
| 0.0726     | 3.2040          | 83    |
| 0.0729     | 3.2187          | 84    |
| 0.0709     | 3.2877          | 85    |
| 0.0703     | 3.3668          | 86    |
| 0.0709     | 3.2290          | 87    |
| 0.0712     | 3.3148          | 88    |
| 0.0697     | 3.2762          | 89    |
| 0.0694     | 3.2083          | 90    |
| 0.0688     | 3.2673          | 91    |
| 0.0694     | 3.2816          | 92    |
| 0.0683     | 3.3135          | 93    |
| 0.0680     | 3.2971          | 94    |
| 0.0681     | 3.2272          | 95    |
| 0.0670     | 3.2317          | 96    |
| 0.0662     | 3.2029          | 97    |
| 0.0656     | 3.2945          | 98    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.1
