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# bertiny-finetuned-finer

This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the finer-139 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0882
- Precision: 0.5339
- Recall: 0.0360
- F1: 0.0675
- Accuracy: 0.9847

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0871        | 1.0   | 11255 | 0.0952          | 0.0       | 0.0    | 0.0    | 0.9843   |
| 0.0864        | 2.0   | 22510 | 0.0895          | 0.7640    | 0.0082 | 0.0162 | 0.9844   |
| 0.0929        | 3.0   | 33765 | 0.0882          | 0.5339    | 0.0360 | 0.0675 | 0.9847   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["finer-139", "nlpaueb/finer-139"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "google/bert_uncased_L-2_H-128_A-2", "model-index": [{"name": "bertiny-finetuned-finer", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "finer-139", "type": "finer-139", "args": "finer-139"}, "metrics": [{"type": "precision", "value": 0.5339285714285714, "name": "Precision"}, {"type": "recall", "value": 0.036011080332409975, "name": "Recall"}, {"type": "f1", "value": 0.06747151077513258, "name": "F1"}, {"type": "accuracy", "value": 0.9847166143263048, "name": "Accuracy"}]}]}]}
transformers pytorch safetensors bert token-classification generated_from_trainer dataset:finer-139 dataset:nlpaueb/finer-139 base_model:google/bert_uncased_L-2_H-128_A-2 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #bert #token-classification #generated_from_trainer #dataset-finer-139 #dataset-nlpaueb/finer-139 #base_model-google/bert_uncased_L-2_H-128_A-2 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bertiny-finetuned-finer
=======================


This model is a fine-tuned version of google/bert\_uncased\_L-2\_H-128\_A-2 on the finer-139 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0882
* Precision: 0.5339
* Recall: 0.0360
* F1: 0.0675
* Accuracy: 0.9847


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #safetensors #bert #token-classification #generated_from_trainer #dataset-finer-139 #dataset-nlpaueb/finer-139 #base_model-google/bert_uncased_L-2_H-128_A-2 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #safetensors #bert #token-classification #generated_from_trainer #dataset-finer-139 #dataset-nlpaueb/finer-139 #base_model-google/bert_uncased_L-2_H-128_A-2 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1