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# depression_suggestion

This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3740

## 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: 64
- 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: 70

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 3    | 60.7965         |
| No log        | 2.0   | 6    | 60.5778         |
| No log        | 3.0   | 9    | 60.1954         |
| No log        | 4.0   | 12   | 59.6487         |
| No log        | 5.0   | 15   | 58.9372         |
| No log        | 6.0   | 18   | 58.0582         |
| No log        | 7.0   | 21   | 57.0106         |
| No log        | 8.0   | 24   | 55.7910         |
| No log        | 9.0   | 27   | 54.3934         |
| No log        | 10.0  | 30   | 52.8099         |
| No log        | 11.0  | 33   | 51.0219         |
| No log        | 12.0  | 36   | 49.0127         |
| No log        | 13.0  | 39   | 46.7522         |
| No log        | 14.0  | 42   | 44.2033         |
| No log        | 15.0  | 45   | 41.3146         |
| No log        | 16.0  | 48   | 37.9982         |
| No log        | 17.0  | 51   | 34.2236         |
| No log        | 18.0  | 54   | 29.8068         |
| No log        | 19.0  | 57   | 24.9750         |
| No log        | 20.0  | 60   | 20.0707         |
| No log        | 21.0  | 63   | 15.5166         |
| No log        | 22.0  | 66   | 12.0328         |
| No log        | 23.0  | 69   | 9.1012          |
| No log        | 24.0  | 72   | 7.2116          |
| No log        | 25.0  | 75   | 6.3149          |
| No log        | 26.0  | 78   | 5.8127          |
| No log        | 27.0  | 81   | 5.4548          |
| No log        | 28.0  | 84   | 5.1684          |
| No log        | 29.0  | 87   | 4.8927          |
| No log        | 30.0  | 90   | 4.6128          |
| No log        | 31.0  | 93   | 4.3782          |
| No log        | 32.0  | 96   | 4.1996          |
| No log        | 33.0  | 99   | 4.0981          |
| No log        | 34.0  | 102  | 4.0022          |
| No log        | 35.0  | 105  | 3.9224          |
| No log        | 36.0  | 108  | 3.8381          |
| No log        | 37.0  | 111  | 3.7660          |
| No log        | 38.0  | 114  | 3.6887          |
| No log        | 39.0  | 117  | 3.6483          |
| No log        | 40.0  | 120  | 3.6020          |
| No log        | 41.0  | 123  | 3.5590          |
| No log        | 42.0  | 126  | 3.5199          |
| No log        | 43.0  | 129  | 3.4646          |
| No log        | 44.0  | 132  | 3.4098          |
| No log        | 45.0  | 135  | 3.3684          |
| No log        | 46.0  | 138  | 3.3290          |
| No log        | 47.0  | 141  | 3.3113          |
| No log        | 48.0  | 144  | 3.3033          |
| No log        | 49.0  | 147  | 3.2928          |
| No log        | 50.0  | 150  | 3.2776          |
| No log        | 51.0  | 153  | 3.2587          |
| No log        | 52.0  | 156  | 3.2487          |
| No log        | 53.0  | 159  | 3.2390          |
| No log        | 54.0  | 162  | 3.2318          |
| No log        | 55.0  | 165  | 3.2311          |
| No log        | 56.0  | 168  | 3.2377          |
| No log        | 57.0  | 171  | 3.2554          |
| No log        | 58.0  | 174  | 3.2720          |
| No log        | 59.0  | 177  | 3.2781          |
| No log        | 60.0  | 180  | 3.2882          |
| No log        | 61.0  | 183  | 3.3089          |
| No log        | 62.0  | 186  | 3.3352          |
| No log        | 63.0  | 189  | 3.3519          |
| No log        | 64.0  | 192  | 3.3233          |
| No log        | 65.0  | 195  | 3.3028          |
| No log        | 66.0  | 198  | 3.3153          |
| No log        | 67.0  | 201  | 3.3422          |
| No log        | 68.0  | 204  | 3.3753          |
| No log        | 69.0  | 207  | 3.4003          |
| No log        | 70.0  | 210  | 3.3740          |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "depression_suggestion", "results": []}]}
transformers pytorch tensorboard gpt2 text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

depression\_suggestion
======================


This model is a fine-tuned version of distilgpt2 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 3.3740


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: 64
* 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: 70


### Training results



### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 64
* 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: 70 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 64
* 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: 70 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 64
* 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: 70### Training results### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1