---
library_name: transformers
tags: []
---

# Model Card for Model ID

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## Validation Loss and Accuracy report:
* **Validation Loss:** 0.11179830832788
* **Validation Accuracy:** 0.9352647152068487

## Classification Report
|                   | **Precision** | **Recall** | **F1-Score** | **Support** |
|-------------------|-----------|--------|----------|---------|
| commodity         | 0.78      | 0.73   | 0.75     | 86      |
| company           | 0.76      | 0.80   | 0.78     | 230     |
| delivery_location| 0.65      | 0.41   | 0.50     | 32      |
| delivery_port     | 0.69      | 0.89   | 0.78     | 309     |
| delivery_state    | 0.71      | 0.63   | 0.67     | 82      |
| incoterms         | 0.77      | 0.88   | 0.82     | 117     |
| measures          | 0.77      | 0.84   | 0.80     | 629     |
| package_type      | 0.95      | 0.94   | 0.95     | 286     |
| pickup_cap        | 0.86      | 0.93   | 0.90     | 107     |
| pickup_location   | 0.71      | 0.77   | 0.74     | 356     |
| pickup_port       | 0.45      | 0.42   | 0.43     | 12      |
| pickup_state      | 0.68      | 0.75   | 0.71     | 71      |
| quantity          | 0.78      | 0.91   | 0.84     | 154     |
| stackable         | 0.94      | 0.98   | 0.96     | 61      |
| total_quantity    | 0.86      | 0.60   | 0.71     | 10      |
| total_volume      | 0.86      | 0.46   | 0.60     | 13      |
| total_weight      | 0.68      | 0.81   | 0.74     | 136     |
| volume            | 0.60      | 0.72   | 0.65     | 43      |
| weight            | 0.67      | 0.58   | 0.62     | 114     |
|                   |           |        |          |         |
| Micro Avg         | 0.76      | 0.82   | 0.79     | 2848    |
| Macro Avg         | 0.75      | 0.74   | 0.73     | 2848    |
| Weighted Avg      | 0.76      | 0.82   | 0.79     | 2848    |



## Model Details

### Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

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- **Language(s) (NLP):** Italian/English
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- **Finetuned from model [optional]:** microsoft/deberta-base

### Model Sources [optional]

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## Uses

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### Direct Use

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### Out-of-Scope Use

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### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

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## Training Details

### Training Data

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### Training Procedure 

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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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## Technical Specifications [optional]

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