
<!-- 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. -->

# camembert-base-NER-favsbot

This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the favsbot dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7433
- Precision: 0.6
- Recall: 0.0121
- F1: 0.0238
- Accuracy: 0.4208

## 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: 1.5e-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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 4    | 2.2915          | 0.1364    | 0.1215 | 0.1285 | 0.3475   |
| No log        | 2.0   | 8    | 2.2230          | 0.2909    | 0.0648 | 0.1060 | 0.4395   |
| No log        | 3.0   | 12   | 2.1573          | 0.4545    | 0.0202 | 0.0388 | 0.4225   |
| No log        | 4.0   | 16   | 2.0961          | 0.0       | 0.0    | 0.0    | 0.4123   |
| No log        | 5.0   | 20   | 2.0426          | 0.0       | 0.0    | 0.0    | 0.4123   |
| No log        | 6.0   | 24   | 1.9965          | 0.0       | 0.0    | 0.0    | 0.4123   |
| No log        | 7.0   | 28   | 1.9575          | 0.0       | 0.0    | 0.0    | 0.4123   |
| No log        | 8.0   | 32   | 1.9233          | 0.0       | 0.0    | 0.0    | 0.4123   |
| No log        | 9.0   | 36   | 1.8933          | 0.0       | 0.0    | 0.0    | 0.4123   |
| No log        | 10.0  | 40   | 1.8674          | 0.0       | 0.0    | 0.0    | 0.4123   |
| No log        | 11.0  | 44   | 1.8441          | 0.0       | 0.0    | 0.0    | 0.4123   |
| No log        | 12.0  | 48   | 1.8240          | 0.0       | 0.0    | 0.0    | 0.4123   |
| No log        | 13.0  | 52   | 1.8060          | 1.0       | 0.0040 | 0.0081 | 0.4140   |
| No log        | 14.0  | 56   | 1.7899          | 1.0       | 0.0040 | 0.0081 | 0.4140   |
| No log        | 15.0  | 60   | 1.7762          | 1.0       | 0.0040 | 0.0081 | 0.4140   |
| No log        | 16.0  | 64   | 1.7647          | 0.5       | 0.0040 | 0.0080 | 0.4157   |
| No log        | 17.0  | 68   | 1.7556          | 0.5       | 0.0040 | 0.0080 | 0.4157   |
| No log        | 18.0  | 72   | 1.7490          | 0.6667    | 0.0081 | 0.016  | 0.4174   |
| No log        | 19.0  | 76   | 1.7449          | 0.75      | 0.0121 | 0.0239 | 0.4191   |
| No log        | 20.0  | 80   | 1.7433          | 0.6       | 0.0121 | 0.0238 | 0.4208   |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["favsbot"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "camembert-base-NER-favsbot", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "favsbot", "type": "favsbot", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "precision", "value": 0.6, "name": "Precision"}, {"type": "recall", "value": 0.012145748987854251, "name": "Recall"}, {"type": "f1", "value": 0.023809523809523808, "name": "F1"}, {"type": "accuracy", "value": 0.42078364565587734, "name": "Accuracy"}]}]}]}
transformers pytorch camembert token-classification generated_from_trainer dataset:favsbot license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #camembert #token-classification #generated_from_trainer #dataset-favsbot #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

camembert-base-NER-favsbot
==========================


This model is a fine-tuned version of camembert-base on the favsbot dataset.
It achieves the following results on the evaluation set:


* Loss: 1.7433
* Precision: 0.6
* Recall: 0.0121
* F1: 0.0238
* Accuracy: 0.4208


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: 1.5e-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: 20


### Training results



### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1.5e-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: 20 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #camembert #token-classification #generated_from_trainer #dataset-favsbot #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1.5e-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: 20 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #camembert #token-classification #generated_from_trainer #dataset-favsbot #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1.5e-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: 20### Training results### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1
* Datasets 2.4.0
* Tokenizers 0.12.1