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# wav2vec2-base-finetuned-manthan_base

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the new_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2246
- Accuracy: 0.9691

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.4725        | 0.98  | 12   | 2.4222          | 0.1057   |
| 2.4501        | 1.98  | 24   | 2.2420          | 0.2784   |
| 2.2977        | 2.98  | 36   | 2.0155          | 0.7603   |
| 2.1331        | 3.98  | 48   | 1.8193          | 0.8582   |
| 1.7927        | 4.98  | 60   | 1.6376          | 0.9459   |
| 1.7226        | 5.98  | 72   | 1.4940          | 0.9613   |
| 1.6036        | 6.98  | 84   | 1.3632          | 0.9665   |
| 1.5181        | 7.98  | 96   | 1.2963          | 0.9562   |
| 1.4384        | 8.98  | 108  | 1.2406          | 0.9742   |
| 1.3339        | 9.98  | 120  | 1.2246          | 0.9691   |


### Framework versions

- Transformers 4.19.0
- Pytorch 1.11.0+cu113
- Datasets 1.14.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["new_dataset"], "metrics": ["accuracy"], "model-index": [{"name": "wav2vec2-base-finetuned-manthan_base", "results": []}]}
transformers pytorch tensorboard wav2vec2 audio-classification generated_from_trainer dataset:new_dataset license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #dataset-new_dataset #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-base-finetuned-manthan\_base
=====================================


This model is a fine-tuned version of facebook/wav2vec2-base on the new\_dataset dataset.
It achieves the following results on the evaluation set:


* Loss: 1.2246
* Accuracy: 0.9691


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: 3e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.19.0
* Pytorch 1.11.0+cu113
* Datasets 1.14.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.19.0
* Pytorch 1.11.0+cu113
* Datasets 1.14.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #dataset-new_dataset #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.19.0
* Pytorch 1.11.0+cu113
* Datasets 1.14.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #dataset-new_dataset #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.19.0
* Pytorch 1.11.0+cu113
* Datasets 1.14.0
* Tokenizers 0.12.1