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# multilingual_minilm-amazon_massive-intent_eu7

This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the [MASSIVE 1.1](https://huggingface.co/datasets/AmazonScience/massive) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8238
- Accuracy: 0.8623
- F1: 0.8623

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 1.3523        | 1.0   | 5038  | 1.3058          | 0.6937   | 0.6937 |
| 0.7842        | 2.0   | 10076 | 0.8434          | 0.8059   | 0.8059 |
| 0.5359        | 3.0   | 15114 | 0.7231          | 0.8302   | 0.8302 |
| 0.4106        | 4.0   | 20152 | 0.7121          | 0.8443   | 0.8443 |
| 0.3294        | 5.0   | 25190 | 0.7366          | 0.8497   | 0.8497 |
| 0.2621        | 6.0   | 30228 | 0.7702          | 0.8528   | 0.8528 |
| 0.2164        | 7.0   | 35266 | 0.7773          | 0.8577   | 0.8577 |
| 0.1756        | 8.0   | 40304 | 0.8080          | 0.8569   | 0.8569 |
| 0.1625        | 9.0   | 45342 | 0.8162          | 0.8624   | 0.8624 |
| 0.1448        | 10.0  | 50380 | 0.8238          | 0.8623   | 0.8623 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
{"language": ["en", "de", "fr", "it", "pt", "es", "pl"], "license": "mit", "tags": ["generated_from_trainer", "nlu", "text-classification"], "datasets": ["AmazonScience/massive"], "metrics": ["accuracy", "f1"], "base_model": "microsoft/Multilingual-MiniLM-L12-H384", "model-index": [{"name": "multilingual_minilm-amazon_massive-intent_eu7", "results": [{"task": {"type": "text-classification", "name": "text-classification"}, "dataset": {"name": "MASSIVE", "type": "AmazonScience/massive", "split": "test"}, "metrics": [{"type": "f1", "value": 0.8623, "name": "F1"}]}]}]}
transformers pytorch tensorboard safetensors bert text-classification generated_from_trainer nlu en de fr it pt es pl dataset:AmazonScience/massive base_model:microsoft/Multilingual-MiniLM-L12-H384 license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #bert #text-classification #generated_from_trainer #nlu #en #de #fr #it #pt #es #pl #dataset-AmazonScience/massive #base_model-microsoft/Multilingual-MiniLM-L12-H384 #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

multilingual\_minilm-amazon\_massive-intent\_eu7
================================================


This model is a fine-tuned version of microsoft/Multilingual-MiniLM-L12-H384 on the MASSIVE 1.1 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.8238
* Accuracy: 0.8623
* F1: 0.8623


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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.1+cu116
* Datasets 2.8.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.1+cu116
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #safetensors #bert #text-classification #generated_from_trainer #nlu #en #de #fr #it #pt #es #pl #dataset-AmazonScience/massive #base_model-microsoft/Multilingual-MiniLM-L12-H384 #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.1+cu116
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #safetensors #bert #text-classification #generated_from_trainer #nlu #en #de #fr #it #pt #es #pl #dataset-AmazonScience/massive #base_model-microsoft/Multilingual-MiniLM-L12-H384 #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.1+cu116
* Datasets 2.8.0
* Tokenizers 0.13.2