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# meeting-sensai

This model is a fine-tuned version of [raquelclemente/tmp_trainer](https://huggingface.co/raquelclemente/tmp_trainer) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 6.7917
- Rouge1: 0.4205
- Rouge2: 0.1795
- Rougel: 0.3536
- Rougelsum: 0.3536

## 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: 0.0005
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| No log        | 2.46  | 5    | 3.6391          | 0.4237 | 0.1996 | 0.3660 | 0.3660    |
| No log        | 4.91  | 10   | 3.4021          | 0.4118 | 0.2142 | 0.3778 | 0.3778    |
| No log        | 7.46  | 15   | 3.5879          | 0.4314 | 0.2218 | 0.3965 | 0.3965    |
| No log        | 9.91  | 20   | 3.8672          | 0.4730 | 0.2043 | 0.4003 | 0.4003    |
| No log        | 12.46 | 25   | 3.8721          | 0.4083 | 0.1885 | 0.3675 | 0.3675    |
| No log        | 14.91 | 30   | 4.0905          | 0.4609 | 0.2105 | 0.4070 | 0.4070    |
| No log        | 17.46 | 35   | 4.4786          | 0.4580 | 0.1856 | 0.3739 | 0.3739    |
| No log        | 19.91 | 40   | 4.9112          | 0.4689 | 0.2573 | 0.4224 | 0.4224    |
| No log        | 22.46 | 45   | 5.2165          | 0.4698 | 0.2151 | 0.4096 | 0.4096    |
| No log        | 24.91 | 50   | 5.5533          | 0.4014 | 0.1837 | 0.3062 | 0.3062    |
| No log        | 27.46 | 55   | 5.8611          | 0.4109 | 0.1854 | 0.3686 | 0.3686    |
| No log        | 29.91 | 60   | 5.8393          | 0.4715 | 0.2370 | 0.4074 | 0.4074    |
| No log        | 32.46 | 65   | 6.1874          | 0.4297 | 0.1898 | 0.3479 | 0.3479    |
| No log        | 34.91 | 70   | 6.3194          | 0.4350 | 0.2207 | 0.3802 | 0.3802    |
| No log        | 37.46 | 75   | 6.2460          | 0.4009 | 0.2056 | 0.3518 | 0.3518    |
| No log        | 39.91 | 80   | 6.5997          | 0.3992 | 0.1869 | 0.3713 | 0.3713    |
| No log        | 42.46 | 85   | 6.5516          | 0.4345 | 0.1928 | 0.3756 | 0.3756    |
| No log        | 44.91 | 90   | 6.5791          | 0.4078 | 0.2036 | 0.3489 | 0.3489    |
| No log        | 47.46 | 95   | 6.7799          | 0.4205 | 0.1795 | 0.3536 | 0.3536    |
| No log        | 49.91 | 100  | 6.7917          | 0.4205 | 0.1795 | 0.3536 | 0.3536    |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "meeting-sensai", "results": []}]}
transformers pytorch tensorboard mt5 text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

meeting-sensai
==============


This model is a fine-tuned version of raquelclemente/tmp\_trainer on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 6.7917
* Rouge1: 0.4205
* Rouge2: 0.1795
* Rougel: 0.3536
* Rougelsum: 0.3536


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: 0.0005
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 5
* num\_epochs: 50


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 5
* num\_epochs: 50 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 5
* num\_epochs: 50 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2