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# AlmogMor345/my_awesome_model

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.3321
- Validation Loss: 1.3458
- Train Precision: 0.0
- Train Recall: 0.0
- Train F1: 0.0
- Train Accuracy: 0.9140
- Epoch: 99

## 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 9, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
| 2.6690     | 2.1130          | 0.0             | 0.0          | 0.0      | 0.9140         | 0     |
| 1.8194     | 1.5602          | 0.0             | 0.0          | 0.0      | 0.9140         | 1     |
| 1.3472     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 2     |
| 1.2568     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 3     |
| 1.3789     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 4     |
| 1.2069     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 5     |
| 1.2804     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 6     |
| 1.2624     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 7     |
| 1.3139     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 8     |
| 1.2605     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 9     |
| 1.2763     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 10    |
| 1.2969     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 11    |
| 1.2780     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 12    |
| 1.1983     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 13    |
| 1.2138     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 14    |
| 1.2663     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 15    |
| 1.2843     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 16    |
| 1.2251     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 17    |
| 1.3197     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 18    |
| 1.2989     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 19    |
| 1.2213     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 20    |
| 1.2360     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 21    |
| 1.2389     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 22    |
| 1.2087     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 23    |
| 1.2446     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 24    |
| 1.2931     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 25    |
| 1.2623     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 26    |
| 1.2253     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 27    |
| 1.2853     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 28    |
| 1.3132     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 29    |
| 1.2183     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 30    |
| 1.2482     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 31    |
| 1.2190     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 32    |
| 1.3112     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 33    |
| 1.2852     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 34    |
| 1.2445     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 35    |
| 1.2528     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 36    |
| 1.2339     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 37    |
| 1.2053     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 38    |
| 1.2210     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 39    |
| 1.2258     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 40    |
| 1.2772     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 41    |
| 1.1695     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 42    |
| 1.2562     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 43    |
| 1.2413     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 44    |
| 1.2390     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 45    |
| 1.3280     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 46    |
| 1.2614     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 47    |
| 1.2350     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 48    |
| 1.3510     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 49    |
| 1.3331     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 50    |
| 1.1755     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 51    |
| 1.2463     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 52    |
| 1.3322     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 53    |
| 1.1857     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 54    |
| 1.3005     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 55    |
| 1.2379     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 56    |
| 1.2763     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 57    |
| 1.2821     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 58    |
| 1.2670     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 59    |
| 1.3589     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 60    |
| 1.3354     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 61    |
| 1.2851     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 62    |
| 1.2417     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 63    |
| 1.2591     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 64    |
| 1.2056     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 65    |
| 1.2569     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 66    |
| 1.3113     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 67    |
| 1.2131     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 68    |
| 1.2395     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 69    |
| 1.2507     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 70    |
| 1.3242     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 71    |
| 1.2997     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 72    |
| 1.2895     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 73    |
| 1.3044     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 74    |
| 1.2696     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 75    |
| 1.2138     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 76    |
| 1.2914     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 77    |
| 1.1968     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 78    |
| 1.3639     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 79    |
| 1.2451     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 80    |
| 1.2949     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 81    |
| 1.2724     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 82    |
| 1.3940     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 83    |
| 1.3156     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 84    |
| 1.3080     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 85    |
| 1.2519     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 86    |
| 1.2222     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 87    |
| 1.2304     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 88    |
| 1.2843     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 89    |
| 1.2523     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 90    |
| 1.2531     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 91    |
| 1.2974     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 92    |
| 1.3301     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 93    |
| 1.2726     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 94    |
| 1.3171     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 95    |
| 1.3577     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 96    |
| 1.2373     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 97    |
| 1.2556     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 98    |
| 1.3321     | 1.3458          | 0.0             | 0.0          | 0.0      | 0.9140         | 99    |


### Framework versions

- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "AlmogMor345/my_awesome_model", "results": []}]}
transformers tf distilbert token-classification generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #distilbert #token-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

AlmogMor345/my\_awesome\_model
==============================


This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 1.3321
* Validation Loss: 1.3458
* Train Precision: 0.0
* Train Recall: 0.0
* Train F1: 0.0
* Train Accuracy: 0.9140
* Epoch: 99


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': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 9, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 9, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #distilbert #token-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 9, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #distilbert #token-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 9, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3