
<!-- 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

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: 0.2359
- Train Accuracy: 0.9271
- Validation Loss: 0.9369
- Validation Accuracy: 0.7394
- Train Lr: 9.938033e-07
- Epoch: 111

## 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': 9.938033e-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    |
| 0.5400     | 0.8094         | 0.8239          | 0.7254              | 9.987258e-07 | 50    |
| 0.5352     | 0.8071         | 0.8190          | 0.7183              | 9.986749e-07 | 51    |
| 0.5141     | 0.8235         | 0.8171          | 0.7183              | 9.986229e-07 | 52    |
| 0.5324     | 0.8024         | 0.8191          | 0.7183              | 9.985699e-07 | 53    |
| 0.5123     | 0.8024         | 0.8279          | 0.7254              | 9.98516e-07  | 54    |
| 0.5151     | 0.8165         | 0.8213          | 0.7113              | 9.984611e-07 | 55    |
| 0.4986     | 0.8118         | 0.8176          | 0.7183              | 9.984052e-07 | 56    |
| 0.4925     | 0.8259         | 0.8208          | 0.7113              | 9.983482e-07 | 57    |
| 0.4848     | 0.8188         | 0.8182          | 0.7042              | 9.982904e-07 | 58    |
| 0.4952     | 0.8282         | 0.8214          | 0.7113              | 9.982315e-07 | 59    |
| 0.4837     | 0.8329         | 0.8192          | 0.7113              | 9.981716e-07 | 60    |
| 0.4513     | 0.8518         | 0.8224          | 0.7183              | 9.981106e-07 | 61    |
| 0.4628     | 0.8376         | 0.8227          | 0.7183              | 9.980488e-07 | 62    |
| 0.4633     | 0.8447         | 0.8246          | 0.7183              | 9.979859e-07 | 63    |
| 0.4472     | 0.8447         | 0.8256          | 0.7113              | 9.97922e-07  | 64    |
| 0.4529     | 0.8306         | 0.8285          | 0.7183              | 9.978571e-07 | 65    |
| 0.4579     | 0.8329         | 0.8331          | 0.7042              | 9.977913e-07 | 66    |
| 0.4326     | 0.8376         | 0.8278          | 0.7113              | 9.977244e-07 | 67    |
| 0.4255     | 0.8447         | 0.8265          | 0.7113              | 9.976566e-07 | 68    |
| 0.4322     | 0.8494         | 0.8293          | 0.7042              | 9.975878e-07 | 69    |
| 0.4189     | 0.8424         | 0.8382          | 0.7042              | 9.97518e-07  | 70    |
| 0.4236     | 0.8494         | 0.8302          | 0.7113              | 9.974472e-07 | 71    |
| 0.4025     | 0.8494         | 0.8364          | 0.7042              | 9.973753e-07 | 72    |
| 0.4225     | 0.8659         | 0.8370          | 0.7113              | 9.973025e-07 | 73    |
| 0.4027     | 0.8541         | 0.8377          | 0.7042              | 9.972288e-07 | 74    |
| 0.4090     | 0.8588         | 0.8381          | 0.7113              | 9.97154e-07  | 75    |
| 0.3887     | 0.8682         | 0.8378          | 0.7042              | 9.970781e-07 | 76    |
| 0.4022     | 0.8706         | 0.8406          | 0.7042              | 9.970014e-07 | 77    |
| 0.3867     | 0.8682         | 0.8457          | 0.7113              | 9.969236e-07 | 78    |
| 0.3689     | 0.8706         | 0.8460          | 0.7113              | 9.968448e-07 | 79    |
| 0.3728     | 0.8729         | 0.8527          | 0.7042              | 9.967652e-07 | 80    |
| 0.3754     | 0.8706         | 0.8525          | 0.7042              | 9.966844e-07 | 81    |
| 0.3580     | 0.8871         | 0.8531          | 0.7113              | 9.966027e-07 | 82    |
| 0.3718     | 0.8659         | 0.8593          | 0.7042              | 9.965199e-07 | 83    |
| 0.3535     | 0.8800         | 0.8593          | 0.7324              | 9.964363e-07 | 84    |
| 0.3342     | 0.8824         | 0.8704          | 0.6972              | 9.963516e-07 | 85    |
| 0.3341     | 0.8918         | 0.8630          | 0.7324              | 9.962658e-07 | 86    |
| 0.3371     | 0.8776         | 0.8698          | 0.7042              | 9.961792e-07 | 87    |
| 0.3338     | 0.8847         | 0.8689          | 0.7042              | 9.960916e-07 | 88    |
| 0.3295     | 0.8776         | 0.8753          | 0.6972              | 9.960029e-07 | 89    |
| 0.3259     | 0.8847         | 0.8696          | 0.7183              | 9.959133e-07 | 90    |
| 0.3290     | 0.8776         | 0.8726          | 0.7183              | 9.958227e-07 | 91    |
| 0.3117     | 0.8988         | 0.8798          | 0.7324              | 9.95731e-07  | 92    |
| 0.3075     | 0.8965         | 0.8836          | 0.7254              | 9.956385e-07 | 93    |
| 0.2905     | 0.9129         | 0.8868          | 0.7183              | 9.95545e-07  | 94    |
| 0.2979     | 0.9153         | 0.8888          | 0.7183              | 9.954504e-07 | 95    |
| 0.3031     | 0.8800         | 0.8956          | 0.7324              | 9.953548e-07 | 96    |
| 0.2883     | 0.9035         | 0.8984          | 0.7042              | 9.952582e-07 | 97    |
| 0.2835     | 0.9106         | 0.8969          | 0.7254              | 9.951607e-07 | 98    |
| 0.2803     | 0.9059         | 0.8998          | 0.7254              | 9.950621e-07 | 99    |
| 0.2812     | 0.9176         | 0.9034          | 0.7254              | 9.949626e-07 | 100   |
| 0.2714     | 0.9153         | 0.9028          | 0.7183              | 9.948621e-07 | 101   |
| 0.2905     | 0.9059         | 0.9144          | 0.7254              | 9.947606e-07 | 102   |
| 0.2631     | 0.9224         | 0.9143          | 0.6972              | 9.946582e-07 | 103   |
| 0.2679     | 0.9176         | 0.9180          | 0.7254              | 9.945547e-07 | 104   |
| 0.2583     | 0.9224         | 0.9206          | 0.7042              | 9.944504e-07 | 105   |
| 0.2613     | 0.9200         | 0.9286          | 0.7254              | 9.94345e-07  | 106   |
| 0.2669     | 0.9012         | 0.9237          | 0.7254              | 9.942386e-07 | 107   |
| 0.2571     | 0.9153         | 0.9351          | 0.7254              | 9.941313e-07 | 108   |
| 0.2570     | 0.9106         | 0.9306          | 0.7324              | 9.940229e-07 | 109   |
| 0.2344     | 0.9200         | 0.9396          | 0.7183              | 9.939135e-07 | 110   |
| 0.2359     | 0.9271         | 0.9369          | 0.7394              | 9.938033e-07 | 111   |


### 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", "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
==================


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: 0.2359
* Train Accuracy: 0.9271
* Validation Loss: 0.9369
* Validation Accuracy: 0.7394
* Train Lr: 9.938033e-07
* Epoch: 111


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': 9.938033e-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': 9.938033e-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': 9.938033e-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