
<!-- 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. -->

# finetuned_bert-base-on-IEMOCAP_4

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3568
- Accuracy: 0.6712

## 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: 2e-05
- 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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2828        | 1.0   | 113  | 1.2221          | 0.4557   |
| 0.9978        | 2.0   | 226  | 0.9164          | 0.6341   |
| 0.6524        | 3.0   | 339  | 0.8095          | 0.6851   |
| 0.5501        | 4.0   | 452  | 0.8434          | 0.6874   |
| 0.4188        | 5.0   | 565  | 0.8785          | 0.6951   |
| 0.3462        | 6.0   | 678  | 0.9251          | 0.7084   |
| 0.2205        | 7.0   | 791  | 1.0525          | 0.6951   |
| 0.2596        | 8.0   | 904  | 1.0655          | 0.7062   |
| 0.242         | 9.0   | 1017 | 1.1137          | 0.7062   |
| 0.1651        | 10.0  | 1130 | 1.1869          | 0.7118   |
| 0.1943        | 11.0  | 1243 | 1.2023          | 0.7029   |
| 0.1442        | 12.0  | 1356 | 1.2443          | 0.6962   |
| 0.1569        | 13.0  | 1469 | 1.2965          | 0.7106   |
| 0.1396        | 14.0  | 1582 | 1.3718          | 0.7007   |
| 0.1002        | 15.0  | 1695 | 1.3720          | 0.7062   |
| 0.1051        | 16.0  | 1808 | 1.3800          | 0.7018   |
| 0.1604        | 17.0  | 1921 | 1.4143          | 0.6962   |
| 0.1211        | 18.0  | 2034 | 1.4186          | 0.7018   |
| 0.1083        | 19.0  | 2147 | 1.4322          | 0.7029   |
| 0.0939        | 20.0  | 2260 | 1.4358          | 0.7007   |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "finetuned_bert-base-on-IEMOCAP_4", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

finetuned\_bert-base-on-IEMOCAP\_4
==================================


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


* Loss: 1.3568
* Accuracy: 0.6712


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: 2e-05
* 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: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* 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: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* 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: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3