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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- text-classification
- emotion
- pytorch
datasets:
- emotion
metrics:
- accuracy
- f1
- precision
- recall
base_model: distilbert-base-cased
model-index:
- name: distilbert-base-cased-emotion
results:
- task:
type: text-classification
name: text-classification
dataset:
name: emotion
type: emotion
config: default
split: validation
metrics:
- type: accuracy
value: 0.9235
name: accuracy
verified: true
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- type: accuracy
value: 0.938
name: Accuracy
verified: true
- type: precision
value: 0.9281100797474869
name: Precision Macro
verified: true
- type: precision
value: 0.938
name: Precision Micro
verified: true
- type: precision
value: 0.9376891512759605
name: Precision Weighted
verified: true
- type: recall
value: 0.9029821552608664
name: Recall Macro
verified: true
- type: recall
value: 0.938
name: Recall Micro
verified: true
- type: recall
value: 0.938
name: Recall Weighted
verified: true
- type: f1
value: 0.9147207975135915
name: F1 Macro
verified: true
- type: f1
value: 0.938
name: F1 Micro
verified: true
- type: f1
value: 0.9373403463117288
name: F1 Weighted
verified: true
- type: loss
value: 0.23682540655136108
name: loss
verified: true
- type: accuracy
value: 0.938
name: Accuracy
verified: true
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- type: precision
value: 0.9281100797474869
name: Precision Macro
verified: true
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- type: precision
value: 0.938
name: Precision Micro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTdiNWE1ZmFmYmE3NDc0YmUyYjRiNGZmMDk5NTg5YWUyOTQyYmNkOWM3M2Y4ZjI4ZWU3Mzk2NTU1YjQxM2QzMiIsInZlcnNpb24iOjF9.9UVnzkkjthoZML84FS8cWbr88JPgG2RQtC7k_I4a3rCC0T6LMsJSoMWCOIz6a6tnpO26q-_x-wM70GzzSanmCg
- type: precision
value: 0.9376891512759605
name: Precision Weighted
verified: true
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- type: recall
value: 0.9029821552608664
name: Recall Macro
verified: true
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- type: recall
value: 0.938
name: Recall Micro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDk4NTE4YjZmZDdlNmI1NDkxYmU4ZjAzODhiNGFhYTAxNGEyNjY2MGE3MWQwNGFkMDhkZjNkYjkzNWQxZDQ1YiIsInZlcnNpb24iOjF9.l2JP6XY0XWRFB6G5A82CQy9-Isn48vAGickkwvhMhcW7cZsPjDTLHg2wyBjD8etcYzU99RdfR9nusSnWxBvxAQ
- type: recall
value: 0.938
name: Recall Weighted
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMTEwNGQ0NDc0NWE2OGUzMjkwMWM2MGRhODViNmIwMDU1NDk3OTdlOWI1N2VlN2JmY2MzYWI4YjJhNDFhYWVhNCIsInZlcnNpb24iOjF9.IV35Ctc1lhxXGP5J3PQxWi6IpWH1ZyZ95yrrca6-EzlF0w3AYL1Bk8q_glolpmrBqUBrJH8AJ07MFN3g77UzCA
- type: f1
value: 0.9147207975135915
name: F1 Macro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDFlNDk2OWUxOWQ5MTY1MTg3MDU2MzA5OGVmYTk2ODgyNDRiNWU5ZDZmYWYzYmMyMTcyZGExMWE1MGQ2Mzk2MyIsInZlcnNpb24iOjF9.GdxhM7wmt4DQucMB21z0ZZx-iOSlf7wYIs01U6dERhXHX4gsDaFIuIFCVNPFZpwerUYUz6Xtsl6jK1v9kkjqBA
- type: f1
value: 0.938
name: F1 Micro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMTFlM2JlYWFhZjQzNGVjNjhhMTQ3MWZlNGFlMDI5YjEyYWQzMmY3MzQ4MmEzYzg0ZjIyZTZlODNmMTRlZWI5OSIsInZlcnNpb24iOjF9.EKJExY6JPzTwnnPzBPTCoDTowYYly6jKw4Qypsj3GKEpzwmqG-hoo5yhyZaoWsRL2hb1W6eHbsZtPdy1HqGLDQ
- type: f1
value: 0.9373403463117288
name: F1 Weighted
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzU1MjI3NTc4N2MxYTI5MjI1OTc3YjFhYjdkZDZmY2MxOTkyYzMzMWIxY2JmNGRkNDg2MTk0YTRiOWJhMTBhNCIsInZlcnNpb24iOjF9.bqFLqztywdiWTm-r7oeQ_R3_VKOTBkyxbL_sZktEE3hsJHYhwLOEVeKD7sqt56gQu_JNYMCz6WGWKRECFKH3Cw
- type: loss
value: 0.23682540655136108
name: loss
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOWZlZjkwNmJjYjAzYzk4ZjU4NzNiYzg1NTU1MGQ3OTFjYmE4MjE5NzNkYzZiZDI0ZmNkM2Y2NGU4ZjJlOThlOSIsInZlcnNpb24iOjF9.mYcz4sdJOmXXMBGW01OSJiKCouKh28AuExj1E7JiPCz-9ri3oRXPkT2fBHgrf0I2ifVEGVSFYckoC8Ymg-cMAw
- task:
type: text-classification
name: Text Classification
dataset:
name: emotion
type: emotion
config: default
split: test
metrics:
- type: accuracy
value: 0.9235
name: Accuracy
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNDdiOWE5ZjI4NmVjN2Y0OWFmNGI2NWU4MTYwMTA5MTFmMjEzOTkyODhhOTEzMzg0OTJmOTM2NGM3YzMxMDAyNCIsInZlcnNpb24iOjF9.SzWJe5bMitRlUb4d0gIX49k_mTC1ADWKDOLdS6TMx3ZGmkMdD6F9-IlmmTunbfVEDQSjweVpv7H7TUcHsBeIBQ
- type: precision
value: 0.89608475565062
name: Precision Macro
verified: true
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- type: precision
value: 0.9235
name: Precision Micro
verified: true
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- type: precision
value: 0.9224273416855945
name: Precision Weighted
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNDNmYWE4MTQxY2FkNTcxMzMyMmQyNmViN2FhMGQxOWYzNGU0MmIyMjhiZmE5ZmYyOWQwMzExZWRiMjRkNzliMyIsInZlcnNpb24iOjF9.6kD-hmPbjJrpAHZY-tFULnufxw118PfMCwj8PBjDKTtSQ_MCTP7iU3KtNe5essy5vDpdBFuA9E9SbrtjW3vnBA
- type: recall
value: 0.8581097243584549
name: Recall Macro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjZjMGJlZmI2NGVmYWIxZjdlYzg1ZjAyNmYwOWQ0NGE2OWI5OGIzMzE5Zjg5Yzg2NTlhZjRkMzE0ZTZjOGUyMCIsInZlcnNpb24iOjF9._r5lQK7hSPCyM9Bz9H5AVactjXzpF3hKW-iB5dco_kmVMhdy_-N00aFQg8XMKa4sL9lmJs0svINUwL5q55vmCw
- type: recall
value: 0.9235
name: Recall Micro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTQyMmZiNDQ1ZDMyZGY5ZWVlOGM0OWMzODhiNWI1NGUzNDJmOWEyM2VjYjhkNGQ4Y2ZmYzMwYjc1NTU4YjY0ZCIsInZlcnNpb24iOjF9.N7SJCOKlRa_3sRFYqiuPZpXmikQ9xuA4uDsKldGVNG6Tg6dffT2fLE9kkTCOQmG3BQzoP-xxjbhjG1gDPe_KCw
- type: recall
value: 0.9235
name: Recall Weighted
verified: true
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- type: f1
value: 0.8746813002250796
name: F1 Macro
verified: true
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- type: f1
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- type: loss
value: 0.32714536786079407
name: loss
verified: true
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---
<!-- 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. -->
# distilbert-base-cased-emotion
**Training:** The model has been trained using the script provided in the following repository https://github.com/MorenoLaQuatra/transformers-tasks-templates
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on [emotion](https://huggingface.co/datasets/emotion) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3272
- Accuracy: 0.9235
- F1: 0.9217
- Precision: 0.9224
- Recall: 0.9235
## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2776 | 1.0 | 500 | 0.2954 | 0.9 | 0.8957 | 0.9031 | 0.9 |
| 0.1887 | 2.0 | 1000 | 0.1716 | 0.934 | 0.9344 | 0.9370 | 0.934 |
| 0.119 | 3.0 | 1500 | 0.1614 | 0.9345 | 0.9342 | 0.9377 | 0.9345 |
| 0.1001 | 4.0 | 2000 | 0.2018 | 0.936 | 0.9353 | 0.9359 | 0.936 |
| 0.0704 | 5.0 | 2500 | 0.1925 | 0.935 | 0.9349 | 0.9354 | 0.935 |
| 0.0471 | 6.0 | 3000 | 0.2369 | 0.938 | 0.9373 | 0.9377 | 0.938 |
| 0.0322 | 7.0 | 3500 | 0.2693 | 0.938 | 0.9382 | 0.9392 | 0.938 |
| 0.0137 | 8.0 | 4000 | 0.2926 | 0.937 | 0.9371 | 0.9372 | 0.937 |
| 0.0099 | 9.0 | 4500 | 0.2964 | 0.9365 | 0.9362 | 0.9362 | 0.9365 |
| 0.0114 | 10.0 | 5000 | 0.3044 | 0.935 | 0.9349 | 0.9350 | 0.935 |
### Framework versions
- Transformers 4.22.1
- Pytorch 1.11.0+cu113
- Datasets 2.0.0
- Tokenizers 0.11.6