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# xtreme_s_w2v2_t5lephone-small_minds14.en-US

This model is a fine-tuned version of [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) on the GOOGLE/XTREME_S - MINDS14.EN-US dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5203
- F1: 0.7526
- Accuracy: 0.7518

## 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: 0.0003
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 150.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:------:|:--------:|
| 2.589         | 3.95   | 20   | 2.6401          | 0.0108 | 0.0816   |
| 2.5223        | 7.95   | 40   | 2.6493          | 0.0339 | 0.0816   |
| 2.5085        | 11.95  | 60   | 2.6236          | 0.0539 | 0.1028   |
| 2.1252        | 15.95  | 80   | 2.5006          | 0.1458 | 0.1667   |
| 1.3711        | 19.95  | 100  | 2.2712          | 0.2344 | 0.2837   |
| 1.5092        | 23.95  | 120  | 2.0599          | 0.3631 | 0.3936   |
| 0.4962        | 27.95  | 140  | 1.8475          | 0.4881 | 0.4894   |
| 0.4169        | 31.95  | 160  | 1.8262          | 0.5358 | 0.5142   |
| 0.1579        | 35.95  | 180  | 1.6481          | 0.5967 | 0.6028   |
| 0.0927        | 39.95  | 200  | 1.4470          | 0.6748 | 0.6560   |
| 0.1363        | 43.95  | 220  | 1.2725          | 0.6836 | 0.6879   |
| 0.1324        | 47.95  | 240  | 1.4330          | 0.6653 | 0.6702   |
| 0.0294        | 51.95  | 260  | 1.2978          | 0.7079 | 0.7163   |
| 0.0326        | 55.95  | 280  | 1.3869          | 0.6823 | 0.6879   |
| 0.0444        | 59.95  | 300  | 1.5764          | 0.7051 | 0.6986   |
| 0.0527        | 63.95  | 320  | 2.2013          | 0.5899 | 0.5851   |
| 0.1542        | 67.95  | 340  | 1.5203          | 0.7053 | 0.6986   |
| 0.0127        | 71.95  | 360  | 1.7149          | 0.7105 | 0.7128   |
| 0.0105        | 75.95  | 380  | 1.2471          | 0.7853 | 0.7837   |
| 0.009         | 79.95  | 400  | 1.5720          | 0.7065 | 0.7057   |
| 0.0081        | 83.95  | 420  | 1.9395          | 0.6656 | 0.6702   |
| 0.2345        | 87.95  | 440  | 1.5704          | 0.7408 | 0.7411   |
| 0.0076        | 91.95  | 460  | 1.4706          | 0.7554 | 0.7589   |
| 0.0064        | 95.95  | 480  | 1.5746          | 0.7491 | 0.7518   |
| 0.3105        | 99.95  | 500  | 1.6824          | 0.7273 | 0.7376   |
| 0.0058        | 103.95 | 520  | 1.3799          | 0.7474 | 0.7624   |
| 0.0055        | 107.95 | 540  | 1.4086          | 0.7350 | 0.7518   |
| 0.0051        | 111.95 | 560  | 1.2832          | 0.7874 | 0.7979   |
| 0.0052        | 115.95 | 580  | 1.3474          | 0.7752 | 0.7801   |
| 0.0046        | 119.95 | 600  | 1.6125          | 0.7451 | 0.7482   |
| 0.0044        | 123.95 | 620  | 1.5927          | 0.7486 | 0.7518   |
| 0.0044        | 127.95 | 640  | 1.5551          | 0.7487 | 0.7518   |
| 0.0041        | 131.95 | 660  | 1.5117          | 0.7631 | 0.7660   |
| 0.0041        | 135.95 | 680  | 1.5210          | 0.7577 | 0.7624   |
| 0.0041        | 139.95 | 700  | 1.5145          | 0.7655 | 0.7660   |
| 0.004         | 143.95 | 720  | 1.5053          | 0.7665 | 0.7660   |
| 0.004         | 147.95 | 740  | 1.5203          | 0.7526 | 0.7518   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1

{"language": ["en-US"], "license": "apache-2.0", "tags": ["minds14", "google/xtreme_s", "generated_from_trainer"], "datasets": ["xtreme_s"], "metrics": ["f1", "accuracy"], "model-index": [{"name": "xtreme_s_w2v2_t5lephone-small_minds14.en-US", "results": []}]}
transformers pytorch tensorboard wav2vec2 minds14 google/xtreme_s generated_from_trainer dataset:xtreme_s license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #minds14 #google/xtreme_s #generated_from_trainer #dataset-xtreme_s #license-apache-2.0 #endpoints_compatible #region-us 

xtreme\_s\_w2v2\_t5lephone-small\_minds14.en-US
===============================================


This model is a fine-tuned version of facebook/wav2vec2-large-lv60 on the GOOGLE/XTREME\_S - MINDS14.EN-US dataset.
It achieves the following results on the evaluation set:


* Loss: 1.5203
* F1: 0.7526
* Accuracy: 0.7518


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: 0.0003
* train\_batch\_size: 2
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 2
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* total\_eval\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 150.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 2
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 2
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* total\_eval\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 150.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #minds14 #google/xtreme_s #generated_from_trainer #dataset-xtreme_s #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 2
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 2
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* total\_eval\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 150.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #minds14 #google/xtreme_s #generated_from_trainer #dataset-xtreme_s #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 2
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 2
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* total\_eval\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 150.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1