
<!-- 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. -->

# Bert_class_1e-06_50epoch_loss

This model is a fine-tuned version of [guoluo/Bert_1.5e_07](https://huggingface.co/guoluo/Bert_1.5e_07) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.5486
- Train Accuracy: 0.7929
- Validation Loss: 0.8168
- Validation Accuracy: 0.7324
- Train Lr: 9.987757e-07
- Epoch: 49

## 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', 'learning_rate': 9.987757e-07, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Train Lr     | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:------------:|:-----:|
| 1.2823     | 0.4776         | 1.0993          | 0.6761              | 1e-06        | 0     |
| 1.0339     | 0.6776         | 0.9839          | 0.6761              | 9.99999e-07  | 1     |
| 0.9705     | 0.6776         | 0.9658          | 0.6761              | 9.999969e-07 | 2     |
| 0.9486     | 0.6776         | 0.9590          | 0.6761              | 9.99994e-07  | 3     |
| 0.9369     | 0.6776         | 0.9544          | 0.6761              | 9.9999e-07   | 4     |
| 0.9332     | 0.6776         | 0.9470          | 0.6761              | 9.99985e-07  | 5     |
| 0.9205     | 0.6776         | 0.9421          | 0.6761              | 9.99979e-07  | 6     |
| 0.9135     | 0.6776         | 0.9374          | 0.6761              | 9.999719e-07 | 7     |
| 0.9113     | 0.6776         | 0.9340          | 0.6761              | 9.99964e-07  | 8     |
| 0.9005     | 0.6776         | 0.9294          | 0.6761              | 9.99955e-07  | 9     |
| 0.8896     | 0.6776         | 0.9242          | 0.6761              | 9.99945e-07  | 10    |
| 0.8746     | 0.6800         | 0.9191          | 0.6761              | 9.99934e-07  | 11    |
| 0.8649     | 0.6824         | 0.9143          | 0.6761              | 9.999219e-07 | 12    |
| 0.8621     | 0.6847         | 0.9095          | 0.6761              | 9.999089e-07 | 13    |
| 0.8506     | 0.6847         | 0.9019          | 0.6761              | 9.99895e-07  | 14    |
| 0.8434     | 0.6800         | 0.8943          | 0.6761              | 9.9988e-07   | 15    |
| 0.8286     | 0.6871         | 0.8885          | 0.6761              | 9.998639e-07 | 16    |
| 0.8239     | 0.6824         | 0.8814          | 0.6761              | 9.998469e-07 | 17    |
| 0.8181     | 0.6894         | 0.8785          | 0.6761              | 9.998289e-07 | 18    |
| 0.7962     | 0.6894         | 0.8731          | 0.6690              | 9.998099e-07 | 19    |
| 0.7908     | 0.7012         | 0.8671          | 0.6690              | 9.997899e-07 | 20    |
| 0.7640     | 0.6988         | 0.8641          | 0.6761              | 9.997689e-07 | 21    |
| 0.7644     | 0.7035         | 0.8590          | 0.6831              | 9.997469e-07 | 22    |
| 0.7512     | 0.7200         | 0.8558          | 0.6831              | 9.99724e-07  | 23    |
| 0.7394     | 0.7200         | 0.8527          | 0.6972              | 9.997e-07    | 24    |
| 0.7366     | 0.7271         | 0.8501          | 0.7113              | 9.99675e-07  | 25    |
| 0.7293     | 0.7247         | 0.8471          | 0.7042              | 9.996489e-07 | 26    |
| 0.7189     | 0.7529         | 0.8479          | 0.7113              | 9.99622e-07  | 27    |
| 0.7077     | 0.7341         | 0.8411          | 0.7183              | 9.99594e-07  | 28    |
| 0.6965     | 0.7671         | 0.8409          | 0.7183              | 9.99565e-07  | 29    |
| 0.6838     | 0.7482         | 0.8372          | 0.7113              | 9.99535e-07  | 30    |
| 0.6835     | 0.7506         | 0.8362          | 0.7113              | 9.99504e-07  | 31    |
| 0.6702     | 0.7812         | 0.8365          | 0.6901              | 9.99472e-07  | 32    |
| 0.6623     | 0.7812         | 0.8323          | 0.7113              | 9.994391e-07 | 33    |
| 0.6565     | 0.7553         | 0.8298          | 0.6972              | 9.994051e-07 | 34    |
| 0.6452     | 0.7718         | 0.8291          | 0.6901              | 9.993701e-07 | 35    |
| 0.6396     | 0.7718         | 0.8284          | 0.7113              | 9.993341e-07 | 36    |
| 0.6299     | 0.7765         | 0.8262          | 0.6831              | 9.992972e-07 | 37    |
| 0.6230     | 0.7953         | 0.8364          | 0.7113              | 9.992592e-07 | 38    |
| 0.6095     | 0.7741         | 0.8233          | 0.7113              | 9.992202e-07 | 39    |
| 0.6193     | 0.7718         | 0.8206          | 0.7113              | 9.991802e-07 | 40    |
| 0.6008     | 0.7859         | 0.8260          | 0.7254              | 9.991393e-07 | 41    |
| 0.5967     | 0.7859         | 0.8199          | 0.7254              | 9.990973e-07 | 42    |
| 0.5883     | 0.7835         | 0.8189          | 0.7183              | 9.990544e-07 | 43    |
| 0.5751     | 0.8071         | 0.8279          | 0.7324              | 9.990104e-07 | 44    |
| 0.5709     | 0.8000         | 0.8204          | 0.7324              | 9.989654e-07 | 45    |
| 0.5697     | 0.8047         | 0.8229          | 0.7254              | 9.989195e-07 | 46    |
| 0.5580     | 0.8094         | 0.8152          | 0.7254              | 9.988726e-07 | 47    |
| 0.5595     | 0.8071         | 0.8275          | 0.7324              | 9.988246e-07 | 48    |
| 0.5486     | 0.7929         | 0.8168          | 0.7324              | 9.987757e-07 | 49    |


### Framework versions

- Transformers 4.30.0.dev0
- TensorFlow 2.9.1
- Datasets 2.8.0
- Tokenizers 0.13.2

{"tags": ["generated_from_keras_callback"], "model-index": [{"name": "Bert_class_1e-06_50epoch_loss", "results": []}]}
transformers tf bert text-classification generated_from_keras_callback autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #bert #text-classification #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 

Bert\_class\_1e-06\_50epoch\_loss
=================================


This model is a fine-tuned version of guoluo/Bert\_1.5e\_07 on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 0.5486
* Train Accuracy: 0.7929
* Validation Loss: 0.8168
* Validation Accuracy: 0.7324
* Train Lr: 9.987757e-07
* Epoch: 49


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', 'learning\_rate': 9.987757e-07, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.30.0.dev0
* TensorFlow 2.9.1
* Datasets 2.8.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 9.987757e-07, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* TensorFlow 2.9.1
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #tf #bert #text-classification #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 9.987757e-07, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* TensorFlow 2.9.1
* Datasets 2.8.0
* Tokenizers 0.13.2